Papers by Jinglin Chen

3 papers
SimulSpeech: End-to-End Simultaneous Speech to Text Translation (2020.acl-main)

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Challenge: SimulSpeech is an end-to-end simultaneous speech to text translation system . conventional approaches to simultaneous speech translation divide the translation process into two stages .
Approach: They develop an end-to-end simultaneous speech to text translation system which translates speech in source language to text in target language concurrently.
Outcome: The proposed system achieves reasonable BLEU scores and lower delay compared to full-sentence translation model.
Faster In-Context Learning for LLMs via N-Gram Trie Speculative Decoding (2025.emnlp-main)

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Challenge: In-Context Learning (ICL) is a key method in prompt engineering, but its long retrieved contexts and limited token throughput will slow reasoning speeds.
Approach: They propose a method that leverages the overlap between context and model output to generate drafts from the context.
Outcome: The proposed method achieves the highest mean speedup on Vicuna-7B, Llama2-7B-Chat, and Llma3-8B-Instruct tasks.
DopplerBAS: Binaural Audio Synthesis Addressing Doppler Effect (2023.findings-acl)

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Challenge: Existing methods for binaural audio synthesis are limited in phase estimation, which is crucial for spatial hearing.
Approach: They propose a method to explicitly address the Doppler effect of the moving speaker . it calculates the radial relative velocity of the speaker in spherical coordinates .
Outcome: The proposed method improves the representative WarpNet and BinauralGrad backbones in phase error metric and reaches a new state of the art (SOTA) it is compared with the current method which is limited in phase estimation .

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