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MedASR: An Open-Source Model for High-Accuracy Medical Dictation
语音识别 | 7.9/10
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Sometin Beta Pass Notin (SBPN): Improving Multilingual ASR for Nigerian Languages via Knowledge Distillation
语音识别 | 6.2/10
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UrduSpeech: A 156-Hour Urdu Speech Corpus with 12-Dimension Paralinguistic Annotations
语音识别 | 7/10
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Improving Automatic Speech Recognition for Speakers Treated for Oral Cancer using Data Augmentation and LLM Error Correction
语音识别 | 6/10
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Mind the Gap: Impact of Synthetic Conversational Data on Multi-Talker ASR and Speaker Diarization
语音识别 说话人分离 | 7.2/10
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A Calculus-Based Framework for Determining Vocabulary Size in End-to-End ASR
语音识别 | 3.9/10
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Refining Pseudo-Audio Prompts with Speech-Text Alignment for Text-Only Domain Adaptation in LLM-Based ASR
语音识别 | 7.5/10
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Vividh-ASR: A Complexity-Tiered Benchmark and Optimization Dynamics for Robust Indic Speech Recognition
语音识别 | 7.0/10
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WARDEN: Endangered Indigenous Language Transcription and Translation with 6 Hours of Training Data
语音识别 | 7.0/10
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Chunkwise Aligners for Streaming Speech Recognition
语音识别 | 6.3/10
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Mechanistic Interpretability of ASR models using Sparse Autoencoders
语音识别 | 5.5/10
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Too Good to Be True: A Study on Modern Automatic Speech Recognition for the Evaluation of Speech Enhancement
语音增强 | 6.6/10
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Bangla-WhisperDiar: Fine-Tuning Whisper and PyAnnote for Bangla Long-Form Speech Recognition and Speaker Diarization
语音识别 说话人日志 | 5.5/10
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Dolphin-CN-Dialect: Where Chinese Dialects Matter
语音识别 | 5.5/10
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Responsible Benchmarking of Fairness for Automatic Speech Recognition
语音识别 | 5.0/10
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Rethinking Entropy Minimization in Test-Time Adaptation for Autoregressive Models
语音识别 | 6.0/10
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The TTS-STT Flywheel: Synthetic Entity-Dense Audio Closes the Indic ASR Gap Where Commercial and Open-Source Systems Fail
语音识别 | 8.5/10
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VocalParse: Towards Unified and Scalable Singing Voice Transcription with Large Audio Language Models
音乐转录 | 7.0/10
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A Comprehensive Analysis of Tokenization and Self-Supervised Learning in End-to-End Automatic Speech Recognition applied on French Language
语音识别 | 7.0/10
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A Paradigm for Interpreting Metrics and Identifying Critical Errors in Automatic Speech Recognition
语音识别 | 6.0/10