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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/sally-sh/vsp-llm

공식 코드

Where Visual Speech Meets Language: VSP-LLM Framework for Efficient and Context-Aware Visual Speech Processing

https://github.com/salute-developers/gigaam

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GigaAM: Efficient Self-Supervised Learner for Speech Recognition

https://github.com/samsad35/code-ancogen

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AnCoGen: Analysis, Control and Generation of Speech with a Masked Autoencoder

https://github.com/samsunglabs/myqasr

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

https://github.com/samsunglabs/summarymixing

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SummaryMixing: A Linear-Complexity Alternative to Self-Attention for Speech Recognition and Understanding

https://github.com/samuael/postprocessed_geez_asr

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Semantically Corrected Amharic Automatic Speech Recognition

https://github.com/santi-pdp/pase

공식 코드

Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks

https://github.com/sarulab-speech/saslaw

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SaSLaW: Dialogue Speech Corpus with Audio-visual Egocentric Information Toward Environment-adaptive Dialogue Speech Synthesis

https://github.com/satvik-venkatesh/you-only-hear-once

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You Only Hear Once: A YOLO-like Algorithm for Audio Segmentation and Sound Event Detection

https://github.com/sberdevices/golos

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Golos: Russian Dataset for Speech Research

https://github.com/scarletcho/KoG2P

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Learning pronunciation from a foreign language in speech synthesis networks

https://github.com/schung039/neural_manifolds_replicaMFT

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Untangling in Invariant Speech Recognition

https://github.com/sciforce/phones-las

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Attention model for articulatory features detection

https://github.com/scufan1990/key-frame-mechanism-for-efficient-conformer

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Key Frame Mechanism For Efficient Conformer Based End-to-end Speech Recognition

https://github.com/sdrobert/more-or-let

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Exploring spectro-temporal features in end-to-end convolutional neural networks

https://github.com/sdrobert/scpc

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

https://github.com/sh-lee-prml/hierspeechpp

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HierSpeech++: Bridging the Gap between Semantic and Acoustic Representation of Speech by Hierarchical Variational Inference for Zero-shot Speech Synthesis

https://github.com/sh-lee-prml/periodwave

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PeriodWave: Multi-Period Flow Matching for High-Fidelity Waveform Generation

https://github.com/sh01k/MeshRIR

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MeshRIR: A Dataset of Room Impulse Responses on Meshed Grid Points For Evaluating Sound Field Analysis and Synthesis Methods

https://github.com/shadynasrat/rdmm

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RDMM: Fine-Tuned LLM Models for On-Device Robotic Decision Making with Enhanced Contextual Awareness in Specific Domains

https://github.com/shajiayu1/OmniDataComposer

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

https://github.com/sharechatai/adima

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ADIMA: Abuse Detection In Multilingual Audio

https://github.com/shark-nlp/attentivemlp

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Attentive Multi-Layer Perceptron for Non-autoregressive Generation

https://github.com/shelton1013/whisper_mce

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

https://github.com/shen9712/universaladapterlearning

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

https://github.com/shinhyeokoh/rwen

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RWEN-TTS: Relation-aware Word Encoding Network for Natural Text-to-Speech Synthesis

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

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

https://github.com/shivammehta25/Matcha-TTS

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Matcha-TTS: A fast TTS architecture with conditional flow matching

https://github.com/shivammehta25/Neural-HMM

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Neural HMMs are all you need (for high-quality attention-free TTS)

https://github.com/shivammehta25/OverFlow

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OverFlow: Putting flows on top of neural transducers for better TTS

https://github.com/shrezaei/Target-Agnostic-Attack

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A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning

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

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Measuring the Accuracy of Automatic Speech Recognition Solutions

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

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

https://github.com/sinaahmadi/cordi

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Language and Speech Technology for Central Kurdish Varieties

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

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

https://github.com/sivannavis/samo

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SAMO: Speaker Attractor Multi-Center One-Class Learning for Voice Anti-Spoofing

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