Implement a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR) pipeline
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Updated
Oct 18, 2020 - HTML
Implement a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR) pipeline
This repository contains Kaldi recipes on the LibriSpeech corpora to extract fMLLR features
End to End Automatic Speech Recognition on Librispeech: Pytorch implementation
An end-to-end speech recognition engine similar to DeepSpeech2
Implementing automatic speech recognition Conformer in PyTorch on Librispeech-100
A simple CRDNN based ASR model for my own understanding of how ASR works and are trained. (Work in progress) If anyone finds any error or have any suggestion please do let me know.
Replication of Jasper speech-to-text network using Intel optimized TensorFlow.
Gender Classification with different Machine Learning models, using the LibriSpeech ASR dataset.
Scripts to generate the reverberant LibriCHiME-5 dataset.
Gender Classification of the speaker from LibriSpeech Dataset
A web-app/library for transcribing speech
Few-shot learning experiments mostly on speaker recognition.
Some approaches based on deep learning to build the acoustic model for an end-to-end automatic speech recognition (ASR) pipeline.
Baselines for the Zero-Resources Speech Challenge using VisuallyGrounded Models of Spoken Language, 2021 edition
Speech Recognition Using Tensorflow
Automatic speech recognition using neural networks
Pytorch implementation of conformer with with training script for end-to-end speech recognition on the LibriSpeech dataset.
Quartznet implementation on pytorch [https://arxiv.org/abs/1910.10261]
End-to-End Speech Recognition using Neural Networks.
Final project for the Speaker Recognition course on Udemy, 机器之心, 深蓝学院 and 语音之家
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