.png){kind=icon}
返回
A probabilistic framework for segment-based speech recognition
.png){kind=icon}
PRE
AI
DOI：10.1016/S0885-2308(03)00006-8.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Most current speech recognizers use an observation space based on a temporal sequence of measurements extracted from fixed-length frames (e.g., Mel-cepstra). Given a hypothetical word or sub-word sequence, the acoustic likelihood computation always involves all observation frames, though the mapping between individual frames and internal recognizer states will depend on the hypothesized segmentation. There is another type of recognizer whose observation space is better represented as a network, or graph, where each arc in the graph corresponds to a hypothesized variable-length segment that is represented by a fixed-dimensional feature. In such feature-based recognizers, each hypothesized segmentation will correspond to a segment sequence, or path, through the overall segment-graph that is associated with a subset of all possible feature vectors in the total observation space. In this work we examine a maximum a posteriori decoding strategy for feature-based recognizers and develop a normalization criterion useful for a segment-based Viterbi or A* search. Experiments are reported for both phonetic, and word recognition tasks. (C) 2003 Elsevier Science Ltd. All rights reserved.
Keyword:
MODELS
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
3.4
论文数:
1.5K
被引数:
2.6K
机构
暂无机构信息
引用论文
A TUTORIAL ON HIDDEN MARKOV-MODELS AND SELECTED APPLICATIONS IN SPEECH RECOGNITION关于语音识别中的隐马尔可夫模型和选定应用的教程.png)
PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
PREAI
分享收藏Disposition of Morphine‐3‐Glucuronide in the Pregnant Rhesus Monkey孕猴体内吗啡-3-葡萄糖苷酸的处理Disposition of Morphine‐3‐Glucuronide in the Pregnant Rhesus Monkey
PREAI
分享收藏
查看更多内容