论文解读
LLM can Read Spectrogram: Encoder-free Speech-Language Modeling
语音识别 | 8.6/10
语音识别
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OmniCap-IF: Benchmarking and Improving Instruction Following Abilities for Omni-Video Captioning
语音生成 | 9.1/10
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Phoneme-First Prediction for LLM-Based Speech Recognition
语音识别 | 6.9/10
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Speaker Group Encoding in Self-supervised Speech Recognition Models
语音识别 | 6.5/10
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Speech Encoder Fusion for LLM-based Automatic Speech Recognition
语音识别 | 7.2/10
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Speech Meets ELF: Audio Conditional Continuous-Target Diffusion for Speech Recognition and Translation
语音识别 | 8.3/10
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Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains
语音识别 | 6.2/10
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TRADE: Transducer-Augmented Decoder for Speech LLM
语音识别 | 7.4/10
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ViP-VL: Vietnamese Self-supervised Speech Pretraining Model with Vector-Quantization Learning
语音识别 | 9.7/10
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A study on the impact of region specific data on the performance of Indic ASR
语音识别 | 7.2/10
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AVI-Bench: Toward Human-like Audio-Visual Intelligence of Omni-MLLMs
语音识别 | 8.8/10
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Bridging Traditional Explainability Methods and Multimodal Multilingual Models: An XAI-Based Analysis
语音识别 | 5.4/10
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Cross-Modal Masking for Robust Silent Speech Synthesis Using sEMG and Lipreading
语音合成 | 7.5/10
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Factors affecting ASR performance: A study using state of the art ASR models in Indic Languages
语音识别 | 6.9/10
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Is Text All You Need? Text as a Universal Information Bottleneck for Speech LLMs
语音识别 | 7.6/10
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Overcoming Decoder Inconsistencies in Whisper for Dravidian and Low-Resource Languages
语音识别 | 6.2/10
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Parameter-Efficient Continual Learning for Automatic Speech Recognition
语音识别 | 8.1/10
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Subtitle-Aligned Fine-Tuning of Whisper for Swiss German ASR: Benchmark Contamination, Convention Mismatch, and an Honest Baseline at 25.6% WER (13.8% cWER)
语音识别 | 8.2/10
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Assessing True Generalisability of Audio-Visual Speech Recognisers
语音识别 | 9.5/10
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Contrastive Training with LLM-generated Near-Misses for Robust Code-Switching Speech Recognition
语音识别 | 7.1/10