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Found 8 papers, 0 papers with code
XCB: an effective contextual biasing approach to bias cross-lingual phrases in speech recognition
Contextualized ASR models have been demonstrated to effectively improve the recognition accuracy of uncommon phrases when a predefined phrase list is available.
An efficient text augmentation approach for contextualized Mandarin speech recognition
Although contextualized automatic speech recognition (ASR) systems are commonly used to improve the recognition of uncommon words, their effectiveness is hindered by the inherent limitations of speech-text data availability.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
MMGER: Multi-modal and Multi-granularity Generative Error Correction with LLM for Joint Accent and Speech Recognition
Accents represent deviations from standard pronunciation norms, and the multi-task learning framework for simultaneous ASR and accent recognition (AR) has effectively addressed the multi-accent scenarios, making it a prominent solution.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Enhancing Lip Reading with Multi-Scale Video and Multi-Encoder
Automatic lip-reading (ALR) aims to automatically transcribe spoken content from a speaker's silent lip motion captured in video.
X-SepFormer: End-to-end Speaker Extraction Network with Explicit Optimization on Speaker Confusion
To mitigate the imperative SC issue, we reformulate the training objective and propose two novel loss schemes that explore the metric of reconstruction improvement performance defined at small chunk-level and leverage the metric associated distribution information.
Improving Target Speaker Extraction with Sparse LDA-transformed Speaker Embeddings
As a practical alternative of speech separation, target speaker extraction (TSE) aims to extract the speech from the desired speaker using additional speaker cue extracted from the speaker.
Joint Speech Activity and Overlap Detection with Multi-Exit Architecture
Overlapped speech detection (OSD) is critical for speech applications in scenario of multi-party conversion.
Speech Enhancement with Perceptually-motivated Optimization and Dual Transformations
To validate the effectiveness of our proposed model, extensive experiments are conducted on the DNS2020 dataset.
