https://github.com/backspacetg/distilxlsr
공식 코드DistilXLSR: A Light Weight Cross-Lingual Speech Representation Model
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Speech Recognition is the task of converting spoken language into text. It involves recognizing the words spoken in an audio recording and transcribing them into a written format. The goal is to accurately transcribe the speech in real-time or from recorded audio, taking into account factors such as accents, speaking speed, and background noise.
<span style="color:grey; opacity: 0.6">( Image credit: SpecAugment )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
DistilXLSR: A Light Weight Cross-Lingual Speech Representation Model
Simul-Whisper: Attention-Guided Streaming Whisper with Truncation Detection
Predicting Affective Vocal Bursts with Finetuned wav2vec 2.0
CHSER: A Dataset and Case Study on Generative Speech Error Correction for Child ASR
Selective Attention Merging for low resource tasks: A case study of Child ASR
Adaptive Computation Modules: Granular Conditional Computation For Efficient Inference
X-Vector based voice activity detection for multi-genre broadcast speech-to-text
Pretraining End-to-End Keyword Search with Automatically Discovered Acoustic Units
Word-level Embeddings for Cross-Task Transfer Learning in Speech Processing
Fast Development of ASR in African Languages using Self Supervised Speech Representation Learning
RFWave: Multi-band Rectified Flow for Audio Waveform Reconstruction
Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems
End-to-End Open Vocabulary Keyword Search With Multilingual Neural Representations
Independent and automatic evaluation of acoustic-to-articulatory inversion models
HK-LegiCoST: Leveraging Non-Verbatim Transcripts for Speech Translation
Self-Supervised Learning for Speech Enhancement through Synthesis
Massively Multilingual Neural Grapheme-to-Phoneme Conversion
End-to-end Spoken Language Understanding with Tree-constrained Pointer Generator
Can Contextual Biasing Remain Effective with Whisper and GPT-2?
Audio-Visual Efficient Conformer for Robust Speech Recognition
Efficient conformer: Progressive downsampling and grouped attention for automatic speech recognition
DiaCorrect: Error Correction Back-end For Speaker Diarization
LightSeq2: Accelerated Training for Transformer-based Models on GPUs
SALMONN: Towards Generic Hearing Abilities for Large Language Models
Revisiting End-to-End Speech-to-Text Translation From Scratch
Improved Child Text-to-Speech Synthesis through Fastpitch-based Transfer Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.