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Key-word Spotting Using Phonetic Distinctive Features Extracted from Output of an LVCSR Engine
| Content Provider | Semantic Scholar |
|---|---|
| Author | Nitta, Tsuneo Iseji, Shingo Fukuda, Takashi Yamada, Hirobumi Katsurada, Kouichi |
| Copyright Year | 2002 |
| Abstract | In this paper, we attempt to adopt a general-purpose LVCSR engine designed for dictation as a spoken dialogue recognition system. In the proposed system, a phoneme string output from the LVCSR engine is converted into a sequence of vectors represented with distinctive features (DF), then keywords assigned by a dialogue manager are detected from the input vector sequence using dynamic time warping (DTW). The proposed system takes advantage of the potential abilities of: (1) precise phoneme discrimination achieved by relaxing the linguistic constraint in the LVCSR engine, and (2) coping with the issues of substitution, deletion and insertion errors by combining a process of conversion from a phoneme into a distinctive feature vector and a key-word spotting process. The proposed system is compared with the general-purpose LVCSR engine in an experiment with a spoken dialogue corpus of a map guidance task and shows significant improvements. Comparative studies on language models and acoustic scoring procedure in key-word detection are also discussed with sub-word model and with confusion matrix, respectively. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.isca-speech.org/archive_open/archive_papers/sspr2003/sspr_map16.pdf |
| Alternate Webpage(s) | http://isca-speech.org/archive_open/archive_papers/sspr2003/sspr_map16.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
