Title
Detecting Repetitions In Spoken Dialogue Systems Using Phonetic Distances
Abstract
Repetitions in Spoken Dialogue Systems can be a symptom of problematic communication. Such repetitions are often due to speech recognition errors, which in turn makes it harder to use the output of the speech recognizer to detect repetitions. In this paper, we combine the alignment score obtained using phonetic distances with dialogue-related features to improve repetition detection. To evaluate the method proposed we compare several alignment techniques from edit distance to DTW-based distance, previously used in Spoken-Term detection tasks. We also compare two different methods to compute the phonetic distance: the first one using the phoneme sequence, and the second one using the distance between the phone posterior vectors. Two different datasets were used in this evaluation: a bus-schedule information system (in English) and a call routing system (in Swedish). The results show that approaches using phoneme distances over-perform approaches using Levenshtein distances between ASR outputs for repetition detection.
Year
Venue
Keywords
2015
16TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2015), VOLS 1-5
spoken dialogue systems, repetition detection, phonetic distance
Field
DocType
Citations 
Computer science,Speech recognition,Natural language processing,Artificial intelligence
Conference
1
PageRank 
References 
Authors
0.36
10
8
Name
Order
Citations
PageRank
José David Lopes1133.04
Giampiero Salvi214821.76
Gabriel Skantze348546.16
Alberto Abad47610.30
Joakim Gustafson539258.37
Fernando Batista611521.04
Raveesh Meena7354.14
Isabel Trancoso8906113.87