查詢結果分析
相關文獻
- Wavelet Transforms for Speech Signal Processing
- A Fast and Efficient Competitive Learning Design Algorithm Based on Weight Vector Training in Transform Domain
- Fractal Extraction from a Mixed FBM Signal Using Discrete Wavelet Transforms
- Computer-Aided Fetus Analysis and Diagnosis System Using Fetal Heart Rate
- 淺談中文字及其輸入、辨識之比較
- 淺談中文字及其輸入、辨識之比較
- 漫談智慧財權之保護
- 應用小波理論於生產策略之快速回應系統
- 中文語音辨識系統
- The Global Minimum of Scalar Quantization Errors by Discrete Wavelet Transforms in Image Compression
頁籤選單縮合
題 名 | Wavelet Transforms for Speech Signal Processing=基於小波轉換之語音信號處理 |
---|---|
作 者 | 王駿發; 陳璽煌; 許志興; | 書刊名 | 中國工程學刊 |
卷 期 | 22:5 1999.09[民88.09] |
頁 次 | 頁549-560 |
專 輯 | 中文語音及語言處理 |
分類號 | 312.23 |
關鍵詞 | 小波轉換; 音高週期搜尋; 子母音分割; 語音辨識; Wavelet transform; Pitch detection; C/V segmentation; Speech recognition; |
語 文 | 英文(English) |
中文摘要 | 小波轉換及其理論為近幾年來相當熱門的研究主題之一,目前小波轉換已被廣泛 地應用在信號處理、影像處理、音訊和語音處理、通信系統以及應用數學等不同的研究領域 。由於小波轉換具有極佳的時域,頻域分析功能以及多重解析的特性,因此非常適合運用在 具有高時變性的語音信號上。本篇論文將首先介紹小波轉換及其理論基礎,並比較小波轉換 與傳統短時間富利葉轉換在信號分析上的差異性,按著本論文將探討小波轉換在語音音高週 期搜尋、子母音分割等基礎語音信號處理上的應用,並分析小波轉換在語音辨識等實際應用 上研究的成果。 |
英文摘要 | The wavelet transform and its theory is one of the most exciting developments of the last decade. In fact, the wavelet transform has been developed independently for various different fields such as signal processing, image processing, audio and speech processing. communication, and mathematics. Due to the efficient time-frequency localization and the multiresolution characteristics of the wavelet representations, the wavelet transforms are quite suitable for processing non-stationary signals such as speech. In this paper, the wavelet transform and its theory will be first introduced, then comparisons between the wavelet transform and the classical short-time Fourier transform approach to signal analysis will be provided. In addition, applying wavelet transforms in determining pitch, and segmenting consonant / vowel (C/V) parts as well as speech recognition will be discussed in this paper. |
本系統中英文摘要資訊取自各篇刊載內容。