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speech

A PyTorch Implementation of End-to-End Models for Speech-to-Text

speech-1

speech-conversion-between-different-modalities

Generative Adversarial Networks for different impaired speech conversions

speech-emotion-classification-with-pytorch

This repository contains PyTorch implementation of 4 different models for classification of emotions of the speech.

speech-resynthesis

An official reimplementation of the method described in the INTERSPEECH 2021 paper - Speech Resynthesis from Discrete Disentangled Self-Supervised Representations.

speech-systhesis-duration-model

use NN to predict duration in speech systhesis

speech-transformer

A PyTorch implementation of Speech Transformer, an End-to-End ASR with Transformer network on Mandarin Chinese.

speech_rankings

A CSRankings-like index for speech researchers

speech_signal_processing_and_classification

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

speech_synthesis

korea univ.

speechalgorithms

Speech Algorithms Collections

speechmetrics

A wrapper around speech quality metrics MOSNet, BSSEval, STOI, PESQ, SRMR, SISDR

speechsplit

Unsupervised Speech Decomposition Via Triple Information Bottleneck

speechsynthesis

음성합성 관련 자료 모음

speedyspeech

spleeter

Deezer source separation library including pretrained models.

spoken-language-identification

方言分类，pytorch

spoken_language_identification

Identify a spoken language using artificial intelligence (LID).

spotlight

Deep recommender models using PyTorch.

sprocket

Voice Conversion Tool Kit

ss-vq-vae

Self-supervised VQ-VAE for One-Shot Music Style Transfer

ss_synthesis

ssast

Code for the AAAI 2022 paper "SSAST: Self-Supervised Audio Spectrogram Transformer".

ssl_speech_restoration

ssp

Speech Signal Processing - a small collection of routines in Python to do signal processing

stam-pytorch

Implementation of STAM (Space Time Attention Model), a pure and simple attention model that reaches SOTA for video classification

stargan-voice-conversion

This is a pytorch implementation of the paper: StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks

style-token_tacotron2

style token with tacotron2

style-transformer

Official implementation for "Style Transformer for Image Inversion and Editing" (CVPR 2022)

styled-lyrics-generator-gpt2

Conditional lyrics generator -> pre-trained GPT2 model fine-tuned on lyrics with features dataset.