Speech Recognition
65개 벤치마크 · 논문 7,133편 · 이 태스크의 논문 보기 →
Benchmarks
LibriSpeech test-clean
LibriSpeech test-other
Switchboard + Hub500
TIMIT
AISHELL-1
WSJ eval92
Common Voice German
swb_hub_500 WER fullSWBCH
TUDA
Common Voice French
Common Voice Spanish
MediaSpeech
SLUE
VietMed
WenetSpeech
Common Voice
EasyCom
GigaSpeech DEV
GigaSpeech TEST
Hub5'00 SwitchBoard
Libri-Light test-clean
Libri-Light test-other
CHiME-6 dev_gss12
LRS3-TED
Tedlium
WSJ dev93
CHiME-6 eval
Common Voice vi
Fongbe audio
SPGISpeech
Speech Commands
VIVOS
WSJ eval93
AISHELL-2
AMI IMH
AMI SDM1
Common Voice English
Common Voice Italian
Europarl-ASR EN MEP-test
GigaSpeech
LibriCSS
TED-LIUM
AISHELL-2 Test Android
AISHELL-2 Test IOS
AISHELL-2 Test Mic
CALLHOME En
CALLHOME Spanish Speech
CAS-VSR-S101
Common Voice Frisian
Common Voice Japanese
Common Voice Portuguese
Common Voice Russian
Hub5'00 CallHome
Hub5'00 FISHER-SWBD
LRS2
Switchboard (300hr)
Switchboard CallHome
Switchboard SWBD
Most implemented
Communication-Efficient Learning of Deep Networks from Decentralized Data
Listen, Attend and Spell
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations
Papers
Hiding Tool Latency in On-Device Cascaded Voice Agent through Speculative Execution
Tool-augmented speech assistants typically serialize automatic speech recognition, large language model inference, and external tool execution. As a result, tool latency is incurred only after the user has finished speak…
Speech RecognitionQ-SPT: Learnable Query-Based Compression for Low-Frame-Rate Speech Tokenization
Neural speech codecs increasingly serve as tokenizers for speech language models (SLMs). Lowering the frame rate reduces the computational and memory costs of SLMs, but makes it difficult to preserve both linguistic info…
Speech RecognitionSHAMS: An Audio-Grounded Pronunciation Benchmark for Levantine Arabic
Levantine Arabic (LA) is spoken by tens of millions of people, creating a pressing need for shared benchmarks to evaluate LA speech-language technologies. Evaluating such technology is particularly challenging given LA's…
Speech RecognitionPruned CTC for Memory-Efficient Large-Vocabulary ASR Training
Connectionist temporal classification (CTC) naturally supports offline and streaming speech recognition with utterance-level supervision, but conventional implementations materialize frame-by-vocabulary activations in me…
Speech RecognitionNVAlign: Direct-Gradient Optimization for Non-Verbal Control in Continuous Autoregressive Flow Matching Text-to-Speech
While modern text-to-speech (TTS) systems generate highly natural speech and support inline non-verbal vocalization (NVV) tags, accurate control over these events remains challenging. A key gap is the lack of established…
Speech RecognitionOmniVChat: Synthesizing, Benchmarking, and Training for Native Audio-Visual Dialogue
We define OmniVChat (Omni Video Chat) as the task of native audio-visual dialogue between a user and an omni model. In OmniVChat, omni models directly and simultaneously receive audio and video from a user and return tex…
Reinforcement LearningSpeech RecognitionVideo Generation