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Speech Recognition

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하위 태스크: 11
평가표: 236
보존된 평가 기록: 398

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>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/aiola-lab/whisper-ner

공식 코드

WhisperNER: Unified Open Named Entity and Speech Recognition

https://github.com/aisaka0v0/ts-whisper

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Extending Whisper with prompt tuning to target-speaker ASR

https://github.com/aixplain/NoRefER

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NoRefER: a Referenceless Quality Metric for Automatic Speech Recognition via Semi-Supervised Language Model Fine-Tuning with Contrastive Learning

https://github.com/ajd12342/textless-s2st

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Textless Speech-to-Speech Translation With Limited Parallel Data

https://github.com/ajd12342/unit-speech-translation

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Textless Speech-to-Speech Translation With Limited Parallel Data

https://github.com/akhilmathurs/libriadapt

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Libri-Adapt: A New Speech Dataset for Unsupervised Domain Adaptation

https://github.com/akreal/bloomzmms

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Teaching a Multilingual Large Language Model to Understand Multilingual Speech via Multi-Instructional Training

https://github.com/albertwy/SWRM

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Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR Errors

https://github.com/alecokas/BiLatticeRNN-Confidence

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Confidence Estimation for Black Box Automatic Speech Recognition Systems Using Lattice Recurrent Neural Networks

https://github.com/alefiury/se-r_2022_challenge_wav2vec2

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Domain Specific Wav2vec 2.0 Fine-tuning For The SE&R 2022 Challenge

https://github.com/alexa/Topical-Chat/tree/master/TopicalChatASR

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Are Neural Open-Domain Dialog Systems Robust to Speech Recognition Errors in the Dialog History? An Empirical Study

https://github.com/alfred0622/hypr

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HypR: A comprehensive study for ASR hypothesis revising with a reference corpus

https://github.com/aliannejadi/castur

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Harnessing Evolution of Multi-Turn Conversations for Effective Answer Retrieval

https://github.com/alibaba-damo-academy/FunASR

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Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition

https://github.com/alibaba-damo-academy/funcodec

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FunCodec: A Fundamental, Reproducible and Integrable Open-source Toolkit for Neural Speech Codec

https://github.com/alibaba-nlp/aishell-ner

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AISHELL-NER: Named Entity Recognition from Chinese Speech

https://github.com/aliyzd95/shemo-modification

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A Persian ASR-based SER: Modification of Sharif Emotional Speech Database and Investigation of Persian Text Corpora

https://github.com/allisonandreyev/WhisperQuantization

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Quantization for OpenAI's Whisper Models: A Comparative Analysis

https://github.com/alphanumericslab/HDLCodeGenerators

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Hardware Synthesis of State-Space Equations; Application to FPGA Implementation of Shallow and Deep Neural Networks

https://github.com/amazon-research/contextual-attention-nlm

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Attention-based Contextual Language Model Adaptation for Speech Recognition

https://github.com/amazon-science/amazon-od3

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Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition

https://github.com/amazon-science/stac-speech-translation

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End-to-End Single-Channel Speaker-Turn Aware Conversational Speech Translation

https://github.com/amforever/fmfcc-a

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FMFCC-A: A Challenging Mandarin Dataset for Synthetic Speech Detection

https://github.com/aminesi/robustness-on-device

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Robustness Analysis of Deep Learning Frameworks on Mobile Platforms

https://github.com/amourwaltz/bayeslms

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Bayesian Neural Network Language Modeling for Speech Recognition

https://github.com/amritkromana/disfluency_detection_from_audio

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Automatic Disfluency Detection from Untranscribed Speech

https://github.com/amujika/Fast-Slow-LSTM

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Fast-Slow Recurrent Neural Networks

https://github.com/andi611/Self-Supervised-Speech-Pretraining-and-Representation-Learning

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TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech

https://github.com/andrespimartin/weighted-x-entropy-asr

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Weighted Cross-entropy for Low-Resource Languages in Multilingual Speech Recognition

https://github.com/andybi7676/reborn-uasr

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REBORN: Reinforcement-Learned Boundary Segmentation with Iterative Training for Unsupervised ASR

https://github.com/anicolson/DeepXi

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Deep Xi as a Front-End for Robust Automatic Speech Recognition

https://github.com/anicolson/SPN-ASI

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Sum-Product Networks for Robust Automatic Speaker Identification

https://github.com/ankilab/spoken-100

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SpokeN-100: A Cross-Lingual Benchmarking Dataset for The Classification of Spoken Numbers in Different Languages

https://github.com/ankitapasad/layerwise-analysis

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Layer-wise Analysis of a Self-supervised Speech Representation Model

https://github.com/anonymousNeurIPS2021submission5254/SupplementaryMaterial

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Muddling Label Regularization: Deep Learning for Tabular Datasets

https://github.com/anshulranjan2004/pyhmm

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Hybrid ASR for Resource-Constrained Robots: HMM - Deep Learning Fusion

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