| 001 Audio and acoustics.mp4 | 37.1 MB | ||
| 001 Audio and acoustics_en.vtt | 8.3 KB | ||
| 001 Data requirement.mp4 | 39.1 MB | ||
| 001 Data requirement_en.vtt | 11.4 KB | ||
| 001 Gaussian mixture models 1.mp4 | 37.7 MB | ||
| 001 Gaussian mixture models 1_en.vtt | 9.8 KB | ||
| 001 Indirect use of neural networks.mp4 | 34.9 MB | ||
| 001 Indirect use of neural networks_en.vtt | 9.3 KB | ||
| 001 Intro to deep learning 1.mp4 | 41.4 MB | ||
| 001 Intro to deep learning 1_en.vtt | 8.6 KB | ||
| 001 Intro to speaker recognition 1.mp4 | 40.6 MB | ||
| 001 Intro to speaker recognition 1_en.vtt | 10 KB | ||
| 001 Short-time analysis.mp4 | 50.9 MB | ||
| 001 Short-time analysis_en.vtt | 14.4 KB | ||
| 001 Should I take this course.mp4 | 66.2 MB | ||
| 001 Should I take this course_en.vtt | 4.3 KB | ||
| 001 What is voice identity.mp4 | 27.4 MB | ||
| 001 What is voice identity_en.vtt | 7.3 KB | ||
| 002 Data preprocessing.mp4 | 39.9 MB | ||
| 002 Data preprocessing_en.vtt | 11.7 KB | ||
| 002 Direct use of neural networks.mp4 | 18.6 MB | ||
| 002 Direct use of neural networks_en.vtt | 5.1 KB | ||
| 002 Expected outcome from this course.mp4 | 11.8 MB | ||
| 002 Expected outcome from this course_en.vtt | 3 KB | ||
| 002 Gaussian mixture models 2.mp4 | 23.6 MB | ||
| 002 Gaussian mixture models 2_en.vtt | 6.7 KB | ||
| 002 Hearing and perception 1.mp4 | 35.7 MB | ||
| 002 Hearing and perception 1_en.vtt | 6.9 KB | ||
| 002 Intro to deep learning 2.mp4 | 38.2 MB | ||
| 002 Intro to deep learning 2_en.vtt | 7.9 KB | ||
| 002 Intro to speaker recognition 2.mp4 | 46.3 MB | ||
| 002 Intro to speaker recognition 2_en.vtt | 11.9 KB | ||
| 002 The earliest voice-id techniques.mp4 | 48.1 MB | ||
| 002 The earliest voice-id techniques_en.vtt | 7.6 KB | ||
| 002 Time domain features.mp4 | 27.8 MB | ||
| 002 Time domain features_en.vtt | 7.6 KB | ||
| 003 Data augmentation 1.mp4 | 36.7 MB | ||
| 003 Data augmentation 1_en.vtt | 10.7 KB | ||
| 003 Feed-forward neural networks.mp4 | 30.3 MB | ||
| 003 Feed-forward neural networks_en.vtt | 6.9 KB | ||
| 003 Frequency domain features.mp4 | 37.5 MB | ||
| 003 Frequency domain features_en.vtt | 9.6 KB | ||
| 003 Gaussian mixture models 3.mp4 | 30.4 MB | ||
| 003 Gaussian mixture models 3_en.vtt | 7.6 KB | ||
| 003 Hearing and perception 2.mp4 | 32.9 MB | ||
| 003 Hearing and perception 2_en.vtt | 6.3 KB | ||
| 003 How to max your win from this course.mp4 | 8.2 MB | ||
| 003 How to max your win from this course_en.vtt | 2.3 KB | ||
| 003 Inference 1.mp4 | 34.9 MB | ||
| 003 Inference 1_en.vtt | 8.6 KB | ||
| 003 System workflow of speaker recognition.mp4 | 29 MB | ||
| 003 System workflow of speaker recognition_en.vtt | 7.2 KB | ||
| 003 The development of voice-id techniques.mp4 | 58.9 MB | ||
| 003 The development of voice-id techniques_en.vtt | 11.7 KB | ||
| 004 Audio signal processing.mp4 | 42.5 MB | ||
| 004 Audio signal processing_en.vtt | 10.2 KB | ||
| 004 Commonly used features.mp4 | 44.2 MB | ||
| 004 Commonly used features_en.vtt | 11.2 KB | ||
| 004 Convolutional neural networks.mp4 | 43.7 MB | ||
| 004 Convolutional neural networks_en.vtt | 11 KB | ||
| 004 Data augmentation 2.mp4 | 39.3 MB | ||
| 004 Data augmentation 2_en.vtt | 11.2 KB | ||
| 004 Inference 2.mp4 | 45.9 MB | ||
| 004 Inference 2_en.vtt | 12.5 KB | ||
| 004 Similarity scoring.mp4 | 42.6 MB | ||
| 004 Similarity scoring_en.vtt | 10.5 KB | ||
| 004 Syllabus.mp4 | 7.7 MB | ||
| 004 Syllabus_en.vtt | 2.1 KB | ||
| 004 The new age of voice-id techniques.mp4 | 39.4 MB | ||
| 004 The new age of voice-id techniques_en.vtt | 6.7 KB | ||
| 004 Universal background model.mp4 | 28.5 MB | ||
| 004 Universal background model_en.vtt | 8.1 KB | ||
| 005 Audio coding and formats.mp4 | 50.5 MB | ||
| 005 Audio coding and formats_en.vtt | 12.5 KB | ||
| 005 Data augmentation 3.mp4 | 26.4 MB | ||
| 005 Data augmentation 3_en.vtt | 6.7 KB | ||
| 005 Evaluation and metrics 1.mp4 | 42.3 MB | ||
| 005 Evaluation and metrics 1_en.vtt | 10.6 KB | ||
| 005 Loss function 1.mp4 | 38.6 MB | ||
| 005 Loss function 1_en.vtt | 10.2 KB | ||
| 005 Recurrent neural networks.mp4 | 39.6 MB | ||
| 005 Recurrent neural networks_en.vtt | 8.8 KB | ||
| 005 Support vector machines 1.mp4 | 22.8 MB | ||
| 005 Support vector machines 1_en.vtt | 6.3 KB | ||
| 006 Attention and transformer.mp4 | 35.1 MB | ||
| 006 Attention and transformer_en.vtt | 9 KB | ||
| 006 Data fusion.mp4 | 32.2 MB | ||
| 006 Data fusion_en.vtt | 7.7 KB | ||
| 006 Evaluation and metrics 2.mp4 | 39.9 MB | ||
| 006 Evaluation and metrics 2_en.vtt | 9.6 KB | ||
| 006 Learning to use SoX.mp4 | 32.3 MB | ||
| 006 Learning to use SoX_en.vtt | 10.1 KB | ||
| 006 Loss function 2.mp4 | 40.3 MB | ||
| 006 Loss function 2_en.vtt | 10.2 KB | ||
| 006 Support vector machines 2.mp4 | 29.8 MB | ||
| 006 Support vector machines 2_en.vtt | 8.1 KB | ||
| 007 Common datasets.mp4 | 32.5 MB | ||
| 007 Common datasets_en.vtt | 6.8 KB | ||
| 007 Deep learning with PyTorch.mp4 | 30.8 MB | ||
| 007 Deep learning with PyTorch_en.vtt | 8.9 KB | ||
| 007 Factor analysis.mp4 | 32 MB | ||
| 007 Factor analysis_en.vtt | 8.8 KB | ||
| 007 Loss function 3.mp4 | 56.9 MB | ||
| 007 Loss function 3_en.vtt | 14.1 KB | ||
| 007 Score normalization.mp4 | 22.6 MB | ||
| 007 Score normalization_en.vtt | 6.3 KB | ||
| 008 Joint factor analysis.mp4 | 19.4 MB | ||
| 008 Joint factor analysis_en.vtt | 4.7 KB | ||
| 009 i-vector.mp4 | 36.1 MB | ||
| 009 i-vector_en.vtt | 8.5 KB | ||
| 40147682-Lenny.mp4 | 25.3 MB | ||
| 40149148-female-audio.wav | 179.6 KB | ||
| 40149154-male-audio.wav | 179.6 KB | ||
| 40259198-speech.wav | 159.7 KB | ||
| 40259202-noise.wav | 311.3 KB | ||
| 40259206-output.wav | 368.7 KB | ||
| 40260372-GMM-1995.pdf | 1.3 MB | ||
| 40260376-GMM-UBM-2000.pdf | 348.1 KB | ||
| 40260378-GMM-SVM-2006.pdf | 321 KB | ||
| 40260380-i-vector-2011.pdf | 1.7 MB | ||
| 40260382-JFA-2008.pdf | 518 KB | ||
| 40260394-Tandem-Deep-Features-2014.PDF | 202 KB | ||
| 40260400-j-vector-2015.PDF | 215 KB | ||
| 40260404-DNN-i-vector-2014.pdf | 373 KB | ||
| 40260430-deep-speaker-2017.pdf | 1.1 MB | ||
| 40260432-d-vector-2014.pdf | 634.7 KB | ||
| 40260436-x-vector-2018.pdf | 269.6 KB | ||
| 40260446-ge2e-2018.pdf | 459 KB | ||
| 40260462-synth2aug-2020.pdf | 249.8 KB | ||
| 40260498-facenet-2015.pdf | 4.5 MB | ||
| 40260504-attention-2017.pdf | 2.1 MB | ||
| 40260612-PLP-1989.pdf | 1.8 MB | ||
| 40260614-PNCC-2016.pdf | 2.1 MB | ||
| 40260684-voiceprint-identification-1962.pdf | 289.4 KB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| external-assets-links.txt | 102.4 B | ||
| ▲ 142 total files | |||
Speaker Recognition | By Award Winning Textbook Author
https://CoursePig.com
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 1.95 GB | Duration: 6h 40m
Audio processing, feature extraction, speaker recognition, deep learning, with coding examples
What you'll learn
Basic concepts and core algorithms in speaker recognition
Audio processing and acoustics
Machine learning and deep learning basics
Coding practice and toolkits for audio and speech
Requirements
College level mathematics
Experience with machine learning or coding will be a plus
Description
This course is an introduction to speaker recognition techniques.
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 1.2 GB | freecoursewb | 5 months | 3 | 2 | |
| 1.9 GB | freecoursewb | 6 months | 3 | 0 | |
| 568.3 MB | freecoursewb | 1 year | 3 | 1 | |
| 1.4 GB | freecoursewb | 2 years | 0 | 0 | |
| 3.8 GB | freecoursewb | 2 years | 4 | 1 |
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