https://github.com/collectivat-dev/ladino_tts
공식 코드Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish
Papers with Code 아카이브
Speech Recognition
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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/coolEphemeroptera/AESRC2020
공식 코드https://github.com/coqui-ai/TTS
공식 코드YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone
https://github.com/craffel/mad
공식 코드Online and Linear-Time Attention by Enforcing Monotonic Alignments
https://github.com/craffel/mocha
공식 코드https://github.com/creatorscan/espnet
공식 코드EAT: Enhanced ASR-TTS for Self-supervised Speech Recognition
https://github.com/cristinalan/flowmur
공식 코드FlowMur: A Stealthy and Practical Audio Backdoor Attack with Limited Knowledge
https://github.com/cs20s030/ehmam
공식 코드EH-MAM: Easy-to-Hard Masked Acoustic Modeling for Self-Supervised Speech Representation Learning
https://github.com/cs20s030/stable_distillation
공식 코드https://github.com/csalt-research/accented-codebooks-asr
공식 코드https://github.com/csikasote/BembaASR
공식 코드BembaSpeech: A Speech Recognition Corpus for the Bemba Language
https://github.com/csikasote/BembaSpeech
공식 코드BembaSpeech: A Speech Recognition Corpus for the Bemba Language
https://github.com/csikasote/bigc
공식 코드https://github.com/ctaguchi/asrcomplexity
공식 코드https://github.com/ctaguchi/killkan
공식 코드Killkan: The Automatic Speech Recognition Dataset for Kichwa with Morphosyntactic Information
https://github.com/cuhealthybrains/mt-llm
공식 코드Large Language Model Can Transcribe Speech in Multi-Talker Scenarios with Versatile Instructions
https://github.com/cwang621/blsp
공식 코드BLSP: Bootstrapping Language-Speech Pre-training via Behavior Alignment of Continuation Writing
https://github.com/cwang621/blsp-emo
공식 코드https://github.com/cyanbx/FastLTS
공식 코드FastLTS: Non-Autoregressive End-to-End Unconstrained Lip-to-Speech Synthesis
https://github.com/cyfer0618/Vaksanca
공식 코드Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling Insights
https://github.com/cyjie429/rego
공식 코드Region-Based Optimization in Continual Learning for Audio Deepfake Detection
https://github.com/cylumn/embodied-multimodal-asr
공식 코드Multimodal Speech Recognition for Language-Guided Embodied Agents
https://github.com/cywang97/StreamingTransformer
공식 코드On the Comparison of Popular End-to-End Models for Large Scale Speech Recognition
https://github.com/cywang97/unispeech
공식 코드UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
https://github.com/czlwang/brainbert
공식 코드BrainBERT: Self-supervised representation learning for intracranial recordings
https://github.com/d-keqi/mlta
공식 코드https://github.com/d223302/subjectiveevaluation
공식 코드Why We Should Report the Details in Subjective Evaluation of TTS More Rigorously
https://github.com/daisyqk/automatic-prosody-annotation
공식 코드Automatic Prosody Annotation with Pre-Trained Text-Speech Model
https://github.com/dalision/modalbiasavsr
공식 코드https://github.com/dan8991/the-sound-of-silence
공식 코드The Sound of Silence: Efficiency of First Digit Features in Synthetic Audio Detection
https://github.com/danielajisafe/ASR-Nigeria-Pidgin
공식 코드Towards End-to-End Training of Automatic Speech Recognition for Nigerian Pidgin
https://github.com/daniellin94144/dual-textless-sqa
공식 코드DUAL: Discrete Spoken Unit Adaptive Learning for Textless Spoken Question Answering
https://github.com/daniellin94144/test-time-adaptation-asr-suta
공식 코드https://github.com/danielshaps/evoclearn_optccv_2022
공식 코드Exploration strategies for articulatory synthesis of complex syllable onsets
https://github.com/danielyuenhx/asdf-differential-testing
공식 코드ASDF: A Differential Testing Framework for Automatic Speech Recognition Systems
https://github.com/danjacobellis/mpq
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.