Speech Recognition
1089 papers with code • 316 benchmarks • 87 datasets
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.
( Image credit: SpecAugment )
Benchmarks
These leaderboards are used to track progress in Speech Recognition
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Libraries
Use these libraries to find Speech Recognition models and implementationsDatasets
MNIST
LibriSpeech
Speech Commands
Common Voice
MuST-C
Libri-Light
AISHELL-1
LRS2
Subtasks
Latest papers
Language and Speech Technology for Central Kurdish Varieties
Kurdish, an Indo-European language spoken by over 30 million speakers, is considered a dialect continuum and known for its diversity in language varieties.
A Cross-Modal Approach to Silent Speech with LLM-Enhanced Recognition
To the best of our knowledge, this work represents the first instance where noninvasive silent speech recognition on an open vocabulary has cleared the threshold of 15% WER, demonstrating that SSIs can be a viable alternative to automatic speech recognition (ASR).
Multilingual Speech Models for Automatic Speech Recognition Exhibit Gender Performance Gaps
g8a9/multilingual-asr-gender-gap
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However, the advantaged group varies between languages.
Where Visual Speech Meets Language: VSP-LLM Framework for Efficient and Context-Aware Visual Speech Processing
sally-sh/vsp-llm
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In visual speech processing, context modeling capability is one of the most important requirements due to the ambiguous nature of lip movements.
HINT: High-quality INPainting Transformer with Mask-Aware Encoding and Enhanced Attention
In this paper, we propose an end-to-end High-quality INpainting Transformer, abbreviated as HINT, which consists of a novel mask-aware pixel-shuffle downsampling module (MPD) to preserve the visible information extracted from the corrupted image while maintaining the integrity of the information available for high-level inferences made within the model.
How do Hyenas deal with Human Speech? Speech Recognition and Translation with ConfHyena
The attention mechanism, a cornerstone of state-of-the-art neural models, faces computational hurdles in processing long sequences due to its quadratic complexity.
DeepCover: Advancing RNN Test Coverage and Online Error Prediction using State Machine Extraction
The proposed methodology along with its assessment metrics contribute to increasing explainability in RNN models by providing a clear representation of their internal decision making process through the extracted SM.
Streaming Sequence Transduction through Dynamic Compression
We introduce STAR (Stream Transduction with Anchor Representations), a novel Transformer-based model designed for efficient sequence-to-sequence transduction over streams.
On Speaker Attribution with SURT
k2-fsa/icefall
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The Streaming Unmixing and Recognition Transducer (SURT) has recently become a popular framework for continuous, streaming, multi-talker speech recognition (ASR).
Towards Event Extraction from Speech with Contextual Clues
While text-based event extraction has been an active research area and has seen successful application in many domains, extracting semantic events from speech directly is an under-explored problem.
