Papers with Code 아카이브
Audio-Visual Speech Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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Audio-visual speech recognition is the task of transcribing a paired audio and visual stream into text.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yl4579/StarGANv2-VC
공식 코드StarGANv2-VC: A Diverse, Unsupervised, Non-parallel Framework for Natural-Sounding Voice Conversion
https://github.com/yl4579/StyleTTS
공식 코드StyleTTS: A Style-Based Generative Model for Natural and Diverse Text-to-Speech Synthesis
https://github.com/yl4579/StyleTTS-VC
공식 코드StyleTTS-VC: One-Shot Voice Conversion by Knowledge Transfer from Style-Based TTS Models
https://github.com/yuchen005/gila
공식 코드Cross-Modal Global Interaction and Local Alignment for Audio-Visual Speech Recognition
https://github.com/yuchen005/mir-gan
공식 코드https://github.com/yuchen005/univpm
공식 코드https://github.com/yuwchen/baspro
공식 코드BASPRO: a balanced script producer for speech corpus collection based on the genetic algorithm
https://github.com/yynil/rwkvtts
공식 코드https://github.com/yzyouzhang/AIR-ASVspoof
공식 코드One-class learning towards generalized voice spoofing detection
https://github.com/yzyouzhang/asvspoof2021_air
공식 코드UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021
https://github.com/zain-jiang/dict-tts
공식 코드Dict-TTS: Learning to Pronounce with Prior Dictionary Knowledge for Text-to-Speech
https://github.com/zhangxinfd/speechtokenizer
공식 코드SpeechTokenizer: Unified Speech Tokenizer for Speech Large Language Models
https://github.com/zhenhouhong/qspeech
공식 코드https://github.com/zhenye234/CoMoSpeech
공식 코드CoMoSpeech: One-Step Speech and Singing Voice Synthesis via Consistency Model
https://github.com/zhenye234/xcodec
공식 코드Codec Does Matter: Exploring the Semantic Shortcoming of Codec for Audio Language Model
https://github.com/zhichaowang970201/text-to-video
공식 코드Text-to-Video: a Two-stage Framework for Zero-shot Identity-agnostic Talking-head Generation
https://github.com/zhikangniu/a-dma
공식 코드Accelerating Diffusion-based Text-to-Speech Model Training with Dual Modality Alignment
https://github.com/zhyuan11/SPE
공식 코드Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding
https://github.com/zqs01/multi-channel-wav2vec2
공식 코드Multichannel AV-wav2vec2: A Framework for Learning Multichannel Multi-Modal Speech Representation
https://github.com/0fengzi0/tacotron
https://github.com/1ytic/warp-rnnt
https://github.com/2023-MindSpore-1/ms-code-15/tree/main/FastSpeech
https://github.com/2023-MindSpore-1/ms-code-15/tree/main/wavenet
https://github.com/2023-MindSpore-1/ms-code-50
https://github.com/2023-MindSpore-1/ms-code-57
LPCNet: Improving Neural Speech Synthesis Through Linear Prediction
https://github.com/2023-MindSpore-4/Code-5/tree/main/IntegralNeuralNetworks
fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit
https://github.com/2023-MindSpore-4/Code8/tree/main/crnn_seq2seq_ocr
The Sequence-to-Sequence Baseline for the Voice Conversion Challenge 2020: Cascading ASR and TTS
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/fastspeech2_conformer
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/2noise/chattts
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
https://github.com/592595/TERA
Defense for Black-box Attacks on Anti-spoofing Models by Self-Supervised Learning
https://github.com/AI-Huang/WaveNet
https://github.com/Amuzak-NTL/ASR-for-Speech-Recog
https://github.com/Baichenjia/Tensorflow-TCN
https://github.com/CSTR-Edinburgh/ophelia
https://github.com/Chasm4359/ProTS
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.