Papers with Code 아카이브
Accented Speech Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/dscripka/openwakeword
Using Speech Synthesis to Train End-to-End Spoken Language Understanding Models
https://github.com/edresson/yourtts
YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone
https://github.com/enhuiz/vall-e
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
https://github.com/erasedwalt/FastSpeech
https://github.com/facebookresearch/denoiser
https://github.com/facebookresearch/sonar
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
https://github.com/fatchord/MelNet
MelNet: A Generative Model for Audio in the Frequency Domain
https://github.com/fatchord/WaveRNN
https://github.com/fd873630/deep_speech_2_korean
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/fishaudio/vocoder
EVA-GAN: Enhanced Various Audio Generation via Scalable Generative Adversarial Networks
https://github.com/foamliu/GST-Tacotron-v2
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
https://github.com/francois-rozet/zuko
https://github.com/freedombenLiu/speech-to-text-wavenet
https://github.com/freshtan/deepspeech2
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/funaudiollm/cv3-eval
CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-training
https://github.com/ga642381/FastSpeech2
https://github.com/galaxycong/hpmdubbing
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/glakshay/Generating-audio-DL
https://github.com/google/lyra
https://github.com/grammatek/iceprondict
https://github.com/hash2430/pitchtron
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
https://github.com/hcy71o/autovocoder
https://github.com/heatz123/naturalspeech
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
https://github.com/hhguo/msmc-tts
https://github.com/hkakitani/deepspeech.pytorch
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/huawei-noah/Speech-Backbones/tree/main/Grad-TTS
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
https://github.com/huggingface/transformers
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/iPRoBe-lab/DeepTalk
DeepTalk: Vocal Style Encoding for Speaker Recognition and Speech Synthesis
https://github.com/ibab/tensorflow-wavenet
https://github.com/imdatsolak/wavenet
https://github.com/inconnu11/Objective-evaluation_speech_synthesis
In Other News: A Bi-style Text-to-speech Model for Synthesizing Newscaster Voice with Limited Data
https://github.com/isadrtdinov/wavenet
https://github.com/ivanvovk/DurIAN
DurIAN: Duration Informed Attention Network For Multimodal Synthesis
https://github.com/ivanvovk/WaveGrad
https://github.com/ivanvovk/durian-pytorch
DurIAN: Duration Informed Attention Network For Multimodal Synthesis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.