Papers with Code 아카이브

Automatic Speech Recognition (ASR)

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 1
평가표: 9
보존된 평가 기록: 20

Automatic Speech Recognition (ASR) involves converting spoken language into written text. It is designed to transcribe spoken words into text in real-time, allowing people to communicate with computers, mobile devices, and other technology using their voice. The goal of Automatic Speech Recognition is to accurately transcribe speech, taking into account variations in accent, pronunciation, and speaking style, as well as background noise and other factors that can affect speech quality.

코드

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

https://github.com/rainavyas/prepend_acoustic_attack

공식 코드

Muting Whisper: A Universal Acoustic Adversarial Attack on Speech Foundation Models

https://github.com/raotnameh/End-to-end-E2E-Named-Entity-Recognition-from-English-Speech

공식 코드

End-to-end Named Entity Recognition from English Speech

https://github.com/raphaelolivier/smoothingasr

공식 코드

Sequential Randomized Smoothing for Adversarially Robust Speech Recognition

https://github.com/raphaelolivier/whisper_attack

공식 코드

There is more than one kind of robustness: Fooling Whisper with adversarial examples

https://github.com/revdotcom/speech-datasets

공식 코드

Earnings-22: A Practical Benchmark for Accents in the Wild

https://github.com/rickltt/punctuation_restoration

공식 코드

A Small and Fast BERT for Chinese Medical Punctuation Restoration

https://github.com/ristea/ccmt

공식 코드

Cascaded Cross-Modal Transformer for Audio-Textual Classification

https://github.com/rithiksachdev/PostASR-Correction-SLT2024

공식 코드

Evolutionary Prompt Design for LLM-Based Post-ASR Error Correction

https://github.com/roger-tseng/speech-parsing

공식 코드

Cascading and Direct Approaches to Unsupervised Constituency Parsing on Spoken Sentences

https://github.com/roudimit/whisper-flamingo

공식 코드

Whisper-Flamingo: Integrating Visual Features into Whisper for Audio-Visual Speech Recognition and Translation

https://github.com/rtaori/Black-Box-Audio

공식 코드

Targeted Adversarial Examples for Black Box Audio Systems

https://github.com/rub-ksv/adrenaline

공식 코드

Exploiting Attention-based Sequence-to-Sequence Architectures for Sound Event Localization

https://github.com/rub-ksv/avtrack

공식 코드

Audiovisual Speaker Tracking using Nonlinear Dynamical Systems with Dynamic Stream Weights

https://github.com/rub-ksv/spatial-stream-weights

공식 코드

Data Fusion for Audiovisual Speaker Localization: Extending Dynamic Stream Weights to the Spatial Domain

https://github.com/rub-ksv/uncertaintyASR

공식 코드

Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification

https://github.com/rub-syssec/dompteur

공식 코드

Dompteur: Taming Audio Adversarial Examples

https://github.com/ruizhecao96/cmgan

공식 코드

CMGAN: Conformer-based Metric GAN for Speech Enhancement

https://github.com/rwth-i6/returnn-experiments

공식 코드

Generating Synthetic Audio Data for Attention-Based Speech Recognition Systems

https://github.com/s1603602/attention_head_removal

공식 코드

Stochastic Attention Head Removal: A simple and effective method for improving Transformer Based ASR Models

https://github.com/sadhusamik/speech_recognition_tools

공식 코드

Radically Old Way of Computing Spectra: Applications in End-to-End ASR

https://github.com/salah-zaiem/PL-groupselection

공식 코드

Pretext Tasks selection for multitask self-supervised speech representation learning

https://github.com/salah-zaiem/Pseudo-Label-Selection

공식 코드

Conditional independence for pretext task selection in Self-supervised speech representation learning

https://github.com/salah-zaiem/speeding_inferences

공식 코드

Fine-tuning Strategies for Faster Inference using Speech Self-Supervised Models: A Comparative Study

https://github.com/samsunglabs/myqasr

공식 코드

A Model for Every User and Budget: Label-Free and Personalized Mixed-Precision Quantization

https://github.com/samsunglabs/summarymixing

공식 코드

Linear Time Complexity Conformers with SummaryMixing for Streaming Speech Recognition

https://github.com/samuael/postprocessed_geez_asr

공식 코드

Semantically Corrected Amharic Automatic Speech Recognition

https://github.com/sberdevices/golos

공식 코드

Golos: Russian Dataset for Speech Research

https://github.com/sdrobert/scpc

공식 코드

Bigger is not Always Better: The Effect of Context Size on Speech Pre-Training

https://github.com/shajiayu1/OmniDataComposer

공식 코드

OmniDataComposer: A Unified Data Structure for Multimodal Data Fusion and Infinite Data Generation

https://github.com/sharechatai/adima

공식 코드

ADIMA: Abuse Detection In Multilingual Audio

https://github.com/shelton1013/whisper_mce

공식 코드

Developing a Multilingual Dataset and Evaluation Metrics for Code-Switching: A Focus on Hong Kong's Polylingual Dynamics

https://github.com/shen9712/universaladapterlearning

공식 코드

Language-Universal Adapter Learning with Knowledge Distillation for End-to-End Multilingual Speech Recognition

https://github.com/shinshoji01/personality-prediction-for-conversation-agents

공식 코드

PersonaTAB: Predicting Personality Traits using Textual, Acoustic, and Behavioral Cues in Fully-Duplex Speech Dialogs

https://github.com/shuffle-project/asr-comparison

공식 코드

Measuring the Accuracy of Automatic Speech Recognition Solutions

https://github.com/shuffle-project/beyond-levenshtein

공식 코드

Beyond Levenshtein: Leveraging Multiple Algorithms for Robust Word Error Rate Computations And Granular Error Classifications

https://github.com/sinica-slam/kaldi-senan

공식 코드

Speech-enhanced and Noise-aware Networks for Robust Speech Recognition

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.