Search Results for author: Po-chun Hsu

Found 17 papers, 11 papers with code

Let's Fuse Step by Step: A Generative Fusion Decoding Algorithm with LLMs for Multi-modal Text Recognition

1 code implementation23 May 2024 Chan-Jan Hsu, Yi-Chang Chen, Feng-Ting Liao, Pei-Chen Ho, Yu-Hsiang Wang, Po-chun Hsu, Da-Shan Shiu

We introduce "Generative Fusion Decoding" (GFD), a novel shallow fusion framework, utilized to integrate Large Language Models (LLMs) into multi-modal text recognition systems such as automatic speech recognition (ASR) and optical character recognition (OCR).

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Breeze-7B Technical Report

no code implementations5 Mar 2024 Chan-Jan Hsu, Chang-Le Liu, Feng-Ting Liao, Po-chun Hsu, Yi-Chang Chen, Da-Shan Shiu

Breeze-7B is an open-source language model based on Mistral-7B, designed to address the need for improved language comprehension and chatbot-oriented capabilities in Traditional Chinese.

Chatbot Language Modelling

Advancing the Evaluation of Traditional Chinese Language Models: Towards a Comprehensive Benchmark Suite

1 code implementation15 Sep 2023 Chan-Jan Hsu, Chang-Le Liu, Feng-Ting Liao, Po-chun Hsu, Yi-Chang Chen, Da-Shan Shiu

In an effort to advance the evaluation of language models in Traditional Chinese and stimulate further research in this field, we have open-sourced our benchmark and opened the model for trial.

Question Answering

Federated Deep Reinforcement Learning for THz-Beam Search with Limited CSI

no code implementations25 Apr 2023 Po-chun Hsu, Li-Hsiang Shen, Chun-Hung Liu, Kai-Ten Feng

Terahertz (THz) communication with ultra-wide available spectrum is a promising technique that can achieve the stringent requirement of high data rate in the next-generation wireless networks, yet its severe propagation attenuation significantly hinders its implementation in practice.


STOP: A dataset for Spoken Task Oriented Semantic Parsing

1 code implementation29 Jun 2022 Paden Tomasello, Akshat Shrivastava, Daniel Lazar, Po-chun Hsu, Duc Le, Adithya Sagar, Ali Elkahky, Jade Copet, Wei-Ning Hsu, Yossi Adi, Robin Algayres, Tu Ahn Nguyen, Emmanuel Dupoux, Luke Zettlemoyer, Abdelrahman Mohamed

Furthermore, in addition to the human-recorded audio, we are releasing a TTS-generated version to benchmark the performance for low-resource domain adaptation of end-to-end SLU systems.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Investigating on Incorporating Pretrained and Learnable Speaker Representations for Multi-Speaker Multi-Style Text-to-Speech

1 code implementation6 Mar 2021 Chung-Ming Chien, Jheng-Hao Lin, Chien-yu Huang, Po-chun Hsu, Hung-Yi Lee

The few-shot multi-speaker multi-style voice cloning task is to synthesize utterances with voice and speaking style similar to a reference speaker given only a few reference samples.

Voice Cloning Voice Conversion

WG-WaveNet: Real-Time High-Fidelity Speech Synthesis without GPU

1 code implementation15 May 2020 Po-chun Hsu, Hung-Yi Lee

As we design a flow-based model that is heavily compressed, the proposed model requires much less computational resources compared to other waveform generation models during both training and inference time; even though the model is highly compressed, the post-filter maintains the quality of generated waveform.

Speech Synthesis Text-To-Speech Synthesis Audio and Speech Processing Sound

Towards Robust Neural Vocoding for Speech Generation: A Survey

no code implementations5 Dec 2019 Po-chun Hsu, Chun-hsuan Wang, Andy T. Liu, Hung-Yi Lee

We found out that the speaker variety is much more important for achieving a universal vocoder than the language.

Speech Synthesis Voice Conversion

Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders

6 code implementations25 Oct 2019 Andy T. Liu, Shu-wen Yang, Po-Han Chi, Po-chun Hsu, Hung-Yi Lee

We present Mockingjay as a new speech representation learning approach, where bidirectional Transformer encoders are pre-trained on a large amount of unlabeled speech.

General Classification Representation Learning +4

Unsupervised End-to-End Learning of Discrete Linguistic Units for Voice Conversion

1 code implementation28 May 2019 Andy T. Liu, Po-chun Hsu, Hung-Yi Lee

We found that the proposed encoding method offers automatic extraction of speech content from speaker style, and is sufficient to cover full linguistic content in a given language.

Decoder Voice Conversion

Rhythm-Flexible Voice Conversion without Parallel Data Using Cycle-GAN over Phoneme Posteriorgram Sequences

1 code implementation9 Aug 2018 Cheng-chieh Yeh, Po-chun Hsu, Ju-chieh Chou, Hung-Yi Lee, Lin-shan Lee

In this way, the length constraint mentioned above is removed to offer rhythm-flexible voice conversion without requiring parallel data.

Sound Audio and Speech Processing

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