Keyword spotting
From Wikipedia, the free encyclopedia
Keyword spotting is a subfield of speech recognition that deals with the identification of keywords in utterances.
There are several types of keyword spotting:
- Keyword spotting in unconstrained speech
- Keyword spotting in isolated word recognition
Keyword spotting in unconstrained speech appears when keywords may not be separated from other words, and no grammar is enforced on the sentence containing them. Some algorithms used for this task are:
- Sliding Window and Garbage Model
- K-best Hypothesis
- Iterative Viterbi Decoding
Keyword spotting in isolated word recognition appears when the keywords are separated from other texts by silences. The main technique that applied in such problems is Dynamic Time Warping.
