title
Part 1-EDA-Audio Classification Project Using Deep Learning

description
In this video we will be developing Audio/ Sound classification using Deep Learning Dataset: https://urbansounddataset.weebly.com/download-urbansound8k.html github: https://github.com/krishnaik06/Audio-Classification ------------------------------------------------------------------------------------------------------------------------ Credits https://mikesmales.medium.com/sound-classification-using-deep-learning-8bc2aa1990b7 ----------------------------------------------------------------------------------------------------------------------- Subscribe my vlogging channel https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw iNeuron is coming up with the Affordable Machine Learning And Deep Learning Master Course. This batch is starting from 10th April and the timing will be 8am to 10am on Saturdays and Sunday and it will be live sessions. The course fees will be 3000 inr+18% GST. Download the syllabus and fill the form to reserve the seat http://ineuron1.viewpage.co/MLRDAPRIL Incase of any queries you can contact the below number. 8788503778 6260726925 9538303385 8660034247 9880055539

detail
{'title': 'Part 1-EDA-Audio Classification Project Using Deep Learning', 'heatmap': [{'end': 613.094, 'start': 579.601, 'weight': 0.782}], 'summary': 'Series presents a project on audio classification using machine learning, covering the urban sound 8k dataset with 8,732 labeled sound excerpts and providing step-by-step guidance on installing libraries, visualizing audio signals, and processing audio data with librosa, along with sound wave analysis and exploratory data analysis (eda) on a dataset of 8732 records.', 'chapters': [{'end': 53.137, 'segs': [{'end': 53.137, 'src': 'embed', 'start': 1.343, 'weight': 0, 'content': [{'end': 3.804, 'text': 'Hello all my name is Krishnayak and welcome to my YouTube channel.', 'start': 1.343, 'duration': 2.461}, {'end': 10.047, 'text': 'So guys we are going to start a very new project which is called as audio or sound classification with the help of machine learning or deep learning.', 'start': 3.844, 'duration': 6.203}, {'end': 16.149, 'text': 'Now this is very, very much important, guys, because many of you had actually requested this yesterday.', 'start': 10.788, 'duration': 5.361}, {'end': 21.833, 'text': 'when we are doing an interview live session, and whenever I am coming live sessions, right at that time, you are telling about audio classification.', 'start': 16.149, 'duration': 5.684}, {'end': 26.056, 'text': 'Now what we are going to do is that we are going to develop this project completely from scratch.', 'start': 22.313, 'duration': 3.743}, {'end': 31.66, 'text': "We'll train it with ANN, CNN and various deep learning models and we'll also try to see the accuracy.", 'start': 26.116, 'duration': 5.544}, {'end': 36.424, 'text': 'Remember these videos will be mostly divided into four parts or three parts mostly.', 'start': 32.621, 'duration': 3.803}, {'end': 41.107, 'text': 'First one is the EDA part, then we have the data pre-processing part and then finally,', 'start': 37.265, 'duration': 3.842}, {'end': 45.03, 'text': "we'll try to create a model and then we'll try to implement this entire thing.", 'start': 41.107, 'duration': 3.923}, {'end': 53.137, 'text': "Again, before going ahead, remember guys, audio, it's not like audio is also a very difficult domain.", 'start': 46.431, 'duration': 6.706}], 'summary': 'Krishnayak launches new project on audio classification using machine learning, in response to viewer requests. project to cover eda, data pre-processing, and model creation.', 'duration': 51.794, 'max_score': 1.343, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y1343.jpg'}], 'start': 1.343, 'title': 'Sound classification project', 'summary': "Discusses a new project on audio classification using machine learning or deep learning, addressing the importance of the topic due to viewer demand and outlining the project's approach of training with ann, cnn, and various deep learning models in 4 parts.", 'chapters': [{'end': 53.137, 'start': 1.343, 'title': 'Sound classification project', 'summary': "Discusses a new project on audio classification using machine learning or deep learning, addressing the importance of the topic due to viewer demand and outlining the project's approach of training with ann, cnn, and various deep learning models in 4 parts.", 'duration': 51.794, 'highlights': ['The project will focus on audio or sound classification using machine learning or deep learning, which was requested by viewers and will be developed from scratch, with training using ANN, CNN, and various deep learning models, with a focus on accuracy.', 'The videos will be divided into EDA part, data pre-processing part, and model creation, reflecting a comprehensive approach to developing the project.', 'The chapter emphasizes the difficulty of the audio domain, highlighting the complexity of the project and the importance of the topic.', 'The project is introduced as a new endeavor on the YouTube channel, indicating a fresh content direction for the audience.']}], 'duration': 51.794, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y1343.jpg', 'highlights': ['The project will focus on audio or sound classification using machine learning or deep learning, which was requested by viewers and will be developed from scratch, with training using ANN, CNN, and various deep learning models, with a focus on accuracy.', 'The videos will be divided into EDA part, data pre-processing part, and model creation, reflecting a comprehensive approach to developing the project.', 'The chapter emphasizes the difficulty of the audio domain, highlighting the complexity of the project and the importance of the topic.', 'The project is introduced as a new endeavor on the YouTube channel, indicating a fresh content direction for the audience.']}, {'end': 221.247, 'segs': [{'end': 128.473, 'src': 'embed', 'start': 102.367, 'weight': 0, 'content': [{'end': 108.589, 'text': 'So this data sets contains 8,732 labeled sound excerpts.', 'start': 102.367, 'duration': 6.222}, {'end': 111.49, 'text': 'For 10 different classes.', 'start': 110.269, 'duration': 1.221}, {'end': 119.592, 'text': 'we have air conditioner, we have car horn, children playing dog bark drilling engine gunshot, jackhammer siren and street music.', 'start': 111.49, 'duration': 8.102}, {'end': 128.473, 'text': "One of the example, if I take and let's see one of the example over here, I have already downloaded this data set in order to download it.", 'start': 120.132, 'duration': 8.341}], 'summary': 'Dataset contains 8,732 labeled sound excerpts across 10 different classes.', 'duration': 26.106, 'max_score': 102.367, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y102367.jpg'}, {'end': 221.247, 'src': 'embed', 'start': 182.78, 'weight': 1, 'content': [{'end': 184.521, 'text': "we'll also try to fine tune the model and all.", 'start': 182.78, 'duration': 1.741}, {'end': 189.722, 'text': 'so first of all, for downloading the data set, just go over here, click on this download form.', 'start': 184.521, 'duration': 5.201}, {'end': 191.943, 'text': "okay, i've given the url anyhow in the eda part.", 'start': 189.722, 'duration': 2.221}, {'end': 195.626, 'text': 'so once you click over here, you have to fill this particular form.', 'start': 192.603, 'duration': 3.023}, {'end': 200.87, 'text': "uh, once you fill this particular form, this data set is somewhere around four to five gb it'll get downloaded.", 'start': 195.626, 'duration': 5.244}, {'end': 205.274, 'text': 'okay, so once you fill this form and just submit it automatically, the downloading will start.', 'start': 200.87, 'duration': 4.404}, {'end': 211.439, 'text': "okay, now let's understand what all things we are actually going to do in this particular, uh, eda part.", 'start': 205.274, 'duration': 6.165}, {'end': 217.023, 'text': 'eda is nothing but exploratory data analysis like how does a sound wave look like?', 'start': 211.439, 'duration': 5.584}, {'end': 221.247, 'text': 'right, because, just understand, this is just like some kind of audio files itself.', 'start': 217.023, 'duration': 4.224}], 'summary': 'Data set download form is around 4 to 5 gb, submitted form starts automatic download. eda involves exploring sound wave-like data.', 'duration': 38.467, 'max_score': 182.78, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y182780.jpg'}], 'start': 53.157, 'title': 'Urban sound classification', 'summary': 'Delves into the significance of audio domain knowledge, introduces the urban sound 8k dataset with 8,732 labeled sound excerpts, and details the process of accessing and analyzing the dataset for audio classification.', 'chapters': [{'end': 221.247, 'start': 53.157, 'title': 'Understanding audio data for urban sound classification', 'summary': 'Discusses the importance of understanding audio domain knowledge, introduces the urban sound 8k dataset containing 8,732 labeled sound excerpts for 10 different classes, and outlines the process of downloading and exploring the dataset for audio classification.', 'duration': 168.09, 'highlights': ['The Urban Sound 8K dataset contains 8,732 labeled sound excerpts for 10 different classes, including air conditioner, car horn, children playing, dog bark, drilling, engine, gunshot, jackhammer, siren, and street music. Quantifiable data: 8,732 labeled sound excerpts for 10 different classes', 'The process of downloading the dataset involves filling a form and submitting it, after which the 4 to 5 GB dataset will be automatically downloaded. Quantifiable data: The dataset size is approximately 4 to 5 GB', 'Exploratory Data Analysis (EDA) will involve understanding how sound waves look and fine-tuning the model for audio classification. Quantifiable data: EDA will involve understanding sound wave patterns']}], 'duration': 168.09, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y53157.jpg', 'highlights': ['The Urban Sound 8K dataset contains 8,732 labeled sound excerpts for 10 different classes', 'The dataset size is approximately 4 to 5 GB', 'Exploratory Data Analysis (EDA) will involve understanding sound wave patterns']}, {'end': 401.393, 'segs': [{'end': 285.656, 'src': 'embed', 'start': 245.672, 'weight': 0, 'content': [{'end': 253.777, 'text': 'this actually helps us to really work well with the sound uh, sound or signals, probably the sound data set itself.', 'start': 245.672, 'duration': 8.105}, {'end': 255.698, 'text': "you'll be able to read that particular signals.", 'start': 253.777, 'duration': 1.921}, {'end': 262.241, 'text': "you'll be able to find out the sample rate or you'll be able to find out how many channels it is and many more things right.", 'start': 255.698, 'duration': 6.543}, {'end': 264.303, 'text': 'so liberalize the library that we are going to use.', 'start': 262.241, 'duration': 2.062}, {'end': 269.186, 'text': 'apart from that, there is also a library in skypie which will actually help us to read the wave signals.', 'start': 264.303, 'duration': 4.883}, {'end': 274.549, 'text': "So usually all these audio files that you're seeing will be in the form of extension as .wav.", 'start': 269.206, 'duration': 5.343}, {'end': 280.453, 'text': "So if I go and see the properties over here, here you'll be having this extension called as .wav files.", 'start': 274.949, 'duration': 5.504}, {'end': 282.174, 'text': "So we'll try to use two libraries.", 'start': 280.833, 'duration': 1.341}, {'end': 285.656, 'text': "For right now, I've just installed Librosa.", 'start': 282.434, 'duration': 3.222}], 'summary': 'Analyzing sound data using libraries like librosa and skypie for .wav files.', 'duration': 39.984, 'max_score': 245.672, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y245672.jpg'}, {'end': 352.837, 'src': 'embed', 'start': 310.129, 'weight': 1, 'content': [{'end': 316.311, 'text': "and I'm going to write each and every line of code in front of you So that you will be able to understand what all things we are doing in the EDM.", 'start': 310.129, 'duration': 6.182}, {'end': 317.832, 'text': 'now Let me do one thing.', 'start': 316.311, 'duration': 1.521}, {'end': 322.394, 'text': 'Let me quickly Go and see one sound data sets.', 'start': 317.892, 'duration': 4.502}, {'end': 327.156, 'text': "probably I'll just go to my audio Now here you can see that.", 'start': 322.394, 'duration': 4.762}, {'end': 328.598, 'text': 'guys, this is my file.', 'start': 327.156, 'duration': 1.442}, {'end': 331.241, 'text': 'audio classification eda.ipynb.', 'start': 328.598, 'duration': 2.643}, {'end': 338.069, 'text': "inside this I have just copied one doc underscore bark outside the folder and I'll just try to test this out,", 'start': 331.241, 'duration': 6.828}, {'end': 340.913, 'text': 'like how the signals of this particular file looks like.', 'start': 338.069, 'duration': 2.844}, {'end': 345.03, 'text': 'So, if I play this, So this is the dog signal right?', 'start': 340.953, 'duration': 4.077}, {'end': 347.032, 'text': 'Dog noise audio right?', 'start': 345.471, 'duration': 1.561}, {'end': 352.837, 'text': "So here what I'm going to do is that I'm just going to display this particular audio file in the form of signals,", 'start': 347.432, 'duration': 5.405}], 'summary': 'Demonstrating audio signal analysis for dog noise classification in edm.', 'duration': 42.708, 'max_score': 310.129, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y310129.jpg'}], 'start': 221.687, 'title': 'Installing libraries and visualizing audio signals', 'summary': 'Provides step-by-step guidance on installing the librosa and skypie libraries for working with sound signals and visualizing audio files using matplotlib.', 'chapters': [{'end': 401.393, 'start': 221.687, 'title': 'Installing libraries and visualizing audio signals', 'summary': 'Discusses the installation of the librosa and skypie libraries for working with sound signals and visualizing audio files using matplotlib, providing step-by-step guidance through code demonstration.', 'duration': 179.706, 'highlights': ['The chapter introduces the installation of the Librosa and Skypie libraries, which enable working with sound signals and reading wave signals, respectively, providing essential functionalities for analyzing sound data sets.', 'The step-by-step code demonstration for visualizing audio signals using Matplotlib ensures clear understanding and implementation of the process, enhancing the learning experience.', 'The author demonstrates the process of importing the Matplotlib library and writing code to display the signals of a specific audio file, offering practical guidance for visualizing audio data.', "The detailed explanation of accessing and displaying the audio signals of a specific file, 'dog_bark', from the 'urban sound 8k' folder enriches the learning experience by providing a hands-on example of visualizing sound data.", "The utilization of Matplotlib to display the signals of the 'dog_bark' audio file enhances the understanding of visualizing sound data, creating a visual representation of the audio signals for analysis."]}], 'duration': 179.706, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y221687.jpg', 'highlights': ['The chapter introduces the installation of the Librosa and Skypie libraries, enabling sound signal analysis.', 'Step-by-step code demonstration for visualizing audio signals using Matplotlib enhances learning.', 'Detailed explanation of accessing and displaying audio signals enriches the learning experience.', "Utilization of Matplotlib to display signals of the 'dog_bark' audio file enhances understanding."]}, {'end': 942.228, 'segs': [{'end': 436.292, 'src': 'embed', 'start': 401.413, 'weight': 3, 'content': [{'end': 406.215, 'text': "Okay. and then what I'm going to do is that I'm also going to install one library.", 'start': 401.413, 'duration': 4.802}, {'end': 415.118, 'text': 'now this library will actually help us to Display some of the graphs in this particular manner of the sound waste.', 'start': 406.215, 'duration': 8.903}, {'end': 420.401, 'text': 'It is called, as I Python dot, display the IPD and then here I am writing IPD.', 'start': 415.118, 'duration': 5.283}, {'end': 425.963, 'text': "Okay, IPD dot audio and here I'm just going to give my file name.", 'start': 420.401, 'duration': 5.562}, {'end': 436.292, 'text': 'and okay, so this audio is basically my function, which will actually help us to load the audio that is in the form of wave file.', 'start': 425.963, 'duration': 10.329}], 'summary': 'Installing a library to display graphs of sound waste using ipython.display.ipd.audio.', 'duration': 34.879, 'max_score': 401.413, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y401413.jpg'}, {'end': 585.506, 'src': 'embed', 'start': 557.448, 'weight': 4, 'content': [{'end': 563.59, 'text': 'Now, if I write this with respect to my sample underscore rate, this will be able to display it now, once I execute it.', 'start': 557.448, 'duration': 6.142}, {'end': 565.151, 'text': "Now again I'm getting one error.", 'start': 563.59, 'duration': 1.561}, {'end': 565.531, 'text': "Let's see.", 'start': 565.191, 'duration': 0.34}, {'end': 572.954, 'text': 'What is that error? It says no for such file or directory urban sound 8k slash doc underscore bark.', 'start': 565.551, 'duration': 7.403}, {'end': 574.336, 'text': "Okay, let's see what is the problem.", 'start': 573.054, 'duration': 1.282}, {'end': 577.078, 'text': "Okay, so probably I've not given the path right.", 'start': 574.736, 'duration': 2.342}, {'end': 579.581, 'text': "Now let's see if I go and write dir.", 'start': 577.238, 'duration': 2.343}, {'end': 585.506, 'text': "Okay, if I execute it, so here I'll be able to see urban sound 8k is there definitely.", 'start': 579.601, 'duration': 5.905}], 'summary': 'Troubleshooting script for displaying sample underscore rate and directory path.', 'duration': 28.058, 'max_score': 557.448, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y557448.jpg'}, {'end': 613.094, 'src': 'heatmap', 'start': 579.601, 'weight': 0.782, 'content': [{'end': 585.506, 'text': "Okay, if I execute it, so here I'll be able to see urban sound 8k is there definitely.", 'start': 579.601, 'duration': 5.905}, {'end': 590.451, 'text': "Now instead of writing this dot doc underscore bark, let's see whether this path is right or not.", 'start': 585.946, 'duration': 4.505}, {'end': 594.856, 'text': 'So urban sound 8K and I have dog underscore bark.', 'start': 590.931, 'duration': 3.925}, {'end': 599.521, 'text': 'This is fine, but here I have to give my extension as .wav.', 'start': 595.336, 'duration': 4.185}, {'end': 603.486, 'text': "Now once I'll go and execute it again and let's see.", 'start': 600.382, 'duration': 3.104}, {'end': 606.75, 'text': 'Yes, now you can see this entire signals properly.', 'start': 604.107, 'duration': 2.643}, {'end': 613.094, 'text': 'Now we are not getting any error because now this audio wanted some kind of sample rate.', 'start': 607.31, 'duration': 5.784}], 'summary': 'Successfully executed code to analyze urban sound 8k data and resolved sample rate error.', 'duration': 33.493, 'max_score': 579.601, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y579601.jpg'}, {'end': 728.246, 'src': 'embed', 'start': 706.074, 'weight': 0, 'content': [{'end': 714.879, 'text': 'when we are reading this information with the help of Librosa, then what happens is that we are reading the signals with the sample rate of 22040..', 'start': 706.074, 'duration': 8.805}, {'end': 724.804, 'text': 'That basically means, in short, whenever Librosa through Librosa, whenever we are reading the data set with respect to some specific audio,', 'start': 714.879, 'duration': 9.925}, {'end': 728.246, 'text': 'we are actually getting the sample rate of 22050..', 'start': 724.804, 'duration': 3.442}], 'summary': 'Librosa reads audio data with a sample rate of 22050.', 'duration': 22.172, 'max_score': 706.074, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y706074.jpg'}], 'start': 401.413, 'title': 'Audio data processing with librosa', 'summary': 'Covers the use of the librosa library for audio data processing, including loading audio files, extracting sample rates, and converting signals into mono channels, emphasizing the importance of sample rates in audio and the role of librosa in standardizing sample rates.', 'chapters': [{'end': 446.921, 'start': 401.413, 'title': 'Installing ipython display library for graphs', 'summary': 'Covers the installation of the ipython display library to visualize sound waves and the function to load audio in wave file format, but encounters an error during execution.', 'duration': 45.508, 'highlights': ['Installing IPython Display Library for visualizing sound waves and loading audio in wave file format', 'Encountering an error during execution']}, {'end': 942.228, 'start': 446.921, 'title': 'Audio data processing with librosa', 'summary': 'Discusses the use of the librosa library for audio data processing, including loading audio files, extracting sample rates, and converting signals into mono channels, highlighting the importance of sample rates in audio and the role of librosa in standardizing sample rates.', 'duration': 495.307, 'highlights': ['The sample rate of the loaded audio file is 22050, which is explained to be the number of times per second a sound is sampled, and Librosa by default reads the signals with a sample rate of 22050. The loaded audio file has a sample rate of 22050, which determines how many times per second a sound is sampled, and Librosa reads the signals with this sample rate by default.', 'Librosa is capable of converting signals into a mono channel and standardizing the sample rate of audio files, such as converting signals into a sample rate of 22050, which simplifies the processing of audio data. Librosa can convert signals into a mono channel and standardize the sample rate of audio files to 22050, simplifying the processing of audio data.', 'The comparison of sample rates between Librosa and Skypie shows a difference, where Librosa reads the sample rate as 22050, while Skypie reads it as 11025, indicating the role of Librosa in standardizing sample rates. The comparison of sample rates between Librosa and Skypie reveals that Librosa reads the sample rate as 22050, while Skypie reads it as 11025, highlighting the role of Librosa in standardizing sample rates.']}], 'duration': 540.815, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y401413.jpg', 'highlights': ['Librosa can convert signals into a mono channel and standardize the sample rate of audio files to 22050, simplifying the processing of audio data.', 'The comparison of sample rates between Librosa and Skypie reveals that Librosa reads the sample rate as 22050, while Skypie reads it as 11025, highlighting the role of Librosa in standardizing sample rates.', 'The loaded audio file has a sample rate of 22050, which determines how many times per second a sound is sampled, and Librosa reads the signals with this sample rate by default.', 'Installing IPython Display Library for visualizing sound waves and loading audio in wave file format', 'Encountering an error during execution']}, {'end': 1528.52, 'segs': [{'end': 967.262, 'src': 'embed', 'start': 942.568, 'weight': 3, 'content': [{'end': 948.151, 'text': "I really want to show you the different, different things with respect to that, right? Now, what I'm going to do quickly is that.", 'start': 942.568, 'duration': 5.583}, {'end': 952.633, 'text': 'Here, we saw that the sample rate with respect to this and with respect to this is 11025.', 'start': 949.211, 'duration': 3.422}, {'end': 955.635, 'text': "Okay, let's see about the wave audio.", 'start': 952.633, 'duration': 3.002}, {'end': 960.778, 'text': 'Now, if I go and see my wave audio, here you will be able to see different, different values.', 'start': 956.055, 'duration': 4.723}, {'end': 961.778, 'text': 'So what are these values?', 'start': 960.818, 'duration': 0.96}, {'end': 967.262, 'text': 'Remember, let me just show you one very nice diagram with the epic pen.', 'start': 962.439, 'duration': 4.823}], 'summary': 'Sample rate is 11025, showing different values in wave audio.', 'duration': 24.694, 'max_score': 942.568, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y942568.jpg'}, {'end': 1134.668, 'src': 'embed', 'start': 1108.182, 'weight': 1, 'content': [{'end': 1117.013, 'text': 'See, Librosa is a library which is now popularly and commonly used for audio signal processing because it actually helps us to do two things.', 'start': 1108.182, 'duration': 8.831}, {'end': 1120.778, 'text': 'One is that it tries to converge the signals.', 'start': 1118.235, 'duration': 2.543}, {'end': 1123.842, 'text': 'It will actually make only one signal, that is the mono one.', 'start': 1121.158, 'duration': 2.684}, {'end': 1134.668, 'text': 'The second thing is that it can represent an audio signals with respect to a normalized pattern between minus 1 to plus 1,', 'start': 1124.642, 'duration': 10.026}], 'summary': 'Librosa is a popular library for audio signal processing, converging signals to mono and normalizing between -1 and +1.', 'duration': 26.486, 'max_score': 1108.182, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y1108182.jpg'}, {'end': 1389.808, 'src': 'embed', 'start': 1358.417, 'weight': 0, 'content': [{'end': 1362.999, 'text': 'It has proper good amounts of most of the categories are having good amount of data set itself.', 'start': 1358.417, 'duration': 4.582}, {'end': 1366.42, 'text': 'okay, now, this was the one thing that i really wanted to check.', 'start': 1363.479, 'duration': 2.941}, {'end': 1367.66, 'text': "let's see some other things.", 'start': 1366.42, 'duration': 1.24}, {'end': 1368.921, 'text': 'what all things we can check.', 'start': 1367.66, 'duration': 1.261}, {'end': 1371.442, 'text': 'okay, this, this information is good enough.', 'start': 1368.921, 'duration': 2.521}, {'end': 1374.823, 'text': 'we know that the data set is not imbalanced itself.', 'start': 1371.442, 'duration': 3.381}, {'end': 1379.644, 'text': 'uh, the next thing that we will do is that we will try to, uh, create a function.', 'start': 1374.823, 'duration': 4.821}, {'end': 1381.165, 'text': 'you know wherein?', 'start': 1379.644, 'duration': 1.521}, {'end': 1389.808, 'text': "wherein? what we'll do is that, see, guys over here, we saw this particular information, right, we, we got the wave sample rate or the wave audio,", 'start': 1381.165, 'duration': 8.643}], 'summary': 'Data set is not imbalanced, creating function to analyze wave sample rate and audio data.', 'duration': 31.391, 'max_score': 1358.417, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y1358417.jpg'}, {'end': 1418.823, 'src': 'embed', 'start': 1395.831, 'weight': 2, 'content': [{'end': 1402.895, 'text': "Now what I'm going to do is that we are going to read all these particular files and probably create this presentation later on.", 'start': 1395.831, 'duration': 7.064}, {'end': 1405.216, 'text': "And also we'll try to write that particular code.", 'start': 1403.335, 'duration': 1.881}, {'end': 1407.618, 'text': 'And that is a part of data preprocessing.', 'start': 1405.697, 'duration': 1.921}, {'end': 1411.74, 'text': 'Here we have just done an EDA, a simple EDA to understand that.', 'start': 1407.678, 'duration': 4.062}, {'end': 1414.982, 'text': 'how does Sound signal look like this kind of waves?', 'start': 1411.74, 'duration': 3.242}, {'end': 1416.042, 'text': "is that what I'll go?", 'start': 1414.982, 'duration': 1.06}, {'end': 1416.983, 'text': 'is that see?', 'start': 1416.042, 'duration': 0.941}, {'end': 1418.823, 'text': "I'll also take some examples.", 'start': 1416.983, 'duration': 1.84}], 'summary': 'Preparing to analyze sound data for data preprocessing, including eda and code writing.', 'duration': 22.992, 'max_score': 1395.831, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y1395831.jpg'}], 'start': 942.568, 'title': 'Sound wave analysis', 'summary': 'Delves into understanding sound waves by discussing the sample rate of 11025 and exploring different wave audio values. it also covers audio signal processing using librosa, including representing audio signals using integer and floating point values and conducting exploratory data analysis (eda) on a dataset of 8732 records across multiple categories.', 'chapters': [{'end': 1028.895, 'start': 942.568, 'title': 'Understanding sound waves', 'summary': 'Discusses the sample rate of 11025 and explores different values associated with wave audio, followed by a brief overview of a sound wave example.', 'duration': 86.327, 'highlights': ['The sample rate with respect to this and with respect to this is 11025.', 'Exploring different values associated with wave audio.', 'Brief overview of a sound wave example.']}, {'end': 1528.52, 'start': 1028.895, 'title': 'Audio signal processing with librosa', 'summary': 'Explores representing audio signals using integer and floating point values, the advantages of using librosa for audio signal processing, and conducting exploratory data analysis (eda) to understand the sound signal patterns and verify the balanced nature of the dataset, totaling 8732 records across multiple categories.', 'duration': 499.625, 'highlights': ['Librosa normalizes audio signal values between -1 to +1, making it advantageous for audio signal processing. Librosa normalizes audio signal values between -1 to +1, providing a standardized pattern for audio signals and making it advantageous for audio signal processing.', 'The dataset contains a total of 8732 records across multiple categories, verifying the balanced nature of the dataset. The dataset contains a total of 8732 records across multiple categories, indicating a balanced nature of the dataset, where most categories have a good amount of data.', "Exploratory data analysis (EDA) is conducted to understand the sound signal patterns and verify the balanced nature of the dataset. Exploratory data analysis (EDA) is conducted to understand the sound signal patterns and verify the balanced nature of the dataset, ensuring the dataset's suitability for further analysis and modeling."]}], 'duration': 585.952, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mHPpCXqQd7Y/pics/mHPpCXqQd7Y942568.jpg', 'highlights': ['The dataset contains a total of 8732 records across multiple categories, verifying the balanced nature of the dataset.', 'Librosa normalizes audio signal values between -1 to +1, making it advantageous for audio signal processing.', 'Exploratory data analysis (EDA) is conducted to understand the sound signal patterns and verify the balanced nature of the dataset.', 'The sample rate with respect to this and with respect to this is 11025.', 'Exploring different values associated with wave audio.']}], 'highlights': ['The project will focus on audio or sound classification using machine learning or deep learning, with a focus on accuracy.', 'The videos will be divided into EDA part, data pre-processing part, and model creation, reflecting a comprehensive approach to developing the project.', 'The chapter emphasizes the difficulty of the audio domain, highlighting the complexity of the project and the importance of the topic.', 'The project is introduced as a new endeavor on the YouTube channel, indicating a fresh content direction for the audience.', 'The Urban Sound 8K dataset contains 8,732 labeled sound excerpts for 10 different classes.', 'The dataset size is approximately 4 to 5 GB.', 'The chapter introduces the installation of the Librosa and Skypie libraries, enabling sound signal analysis.', 'Step-by-step code demonstration for visualizing audio signals using Matplotlib enhances learning.', 'Librosa can convert signals into a mono channel and standardize the sample rate of audio files to 22050, simplifying the processing of audio data.', 'The comparison of sample rates between Librosa and Skypie reveals that Librosa reads the sample rate as 22050, while Skypie reads it as 11025, highlighting the role of Librosa in standardizing sample rates.', 'The dataset contains a total of 8732 records across multiple categories, verifying the balanced nature of the dataset.', 'Librosa normalizes audio signal values between -1 to +1, making it advantageous for audio signal processing.']}