https://github.com/hlt-mt/fbk-fairseq
공식 코드Who Are We Talking About? Handling Person Names in Speech Translation
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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.
Who Are We Talking About? Handling Person Names in Speech Translation
MOSEL: 950,000 Hours of Speech Data for Open-Source Speech Foundation Model Training on EU Languages
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset
CI-AVSR: A Cantonese Audio-Visual Speech Dataset for In-car Command Recognition
Homophone Disambiguation Reveals Patterns of Context Mixing in Speech Transformers
Token-Level Supervised Contrastive Learning for Punctuation Restoration
Less Peaky and More Accurate CTC Forced Alignment by Label Priors
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
Datasets: A Community Library for Natural Language Processing
Distil-Whisper: Robust Knowledge Distillation via Large-Scale Pseudo Labelling
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units
Big model only for hard audios: Sample dependent Whisper model selection for efficient inferences
CoGenAV: Versatile Audio-Visual Representation Learning via Contrastive-Generative Synchronization
Perception and Semantic Aware Regularization for Sequential Confidence Calibration
MathSpeech: Leveraging Small LMs for Accurate Conversion in Mathematical Speech-to-Formula
HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models
A Change of Heart: Improving Speech Emotion Recognition through Speech-to-Text Modality Conversion
Large Language Models Are Read/Write Policy-Makers for Simultaneous Generation
Back Translation for Speech-to-text Translation Without Transcripts
LLaMA-Omni2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech Synthesis
Efficient Speech Language Modeling via Energy Distance in Continuous Latent Space
StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task Learning
Bayesian Parameter-Efficient Fine-Tuning for Overcoming Catastrophic Forgetting
A Comparison of Methods for OOV-word Recognition on a New Public Dataset
Unsupervised Rhythm and Voice Conversion to Improve ASR on Dysarthric Speech
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.