Add to ORKGA major problem with speech recognition interfaces is the detection and correct rejection of words that lie outside of the command vocabulary. Given the limited resources pro-vided to an interface, any method that is used to detect out-of-vocabulary (OOV) words should ideally require mini-mal computational resources. A new utterance verifier is proposed which detects OOV words efficiently using con-fidence measures calculated for additional words in the N-Best list. This approach can be used with any existing con-fidence measure. We implement this utterance verifier with three different confidence measures and obtain a 3-16 % im-provement over their standard implementation. 1
The approach proposed is an alternative to the tradi-tional architecture of Spoken Dialogue Systems ...
We propose a new confidence score for decoding and verification. Since the traditional log likelihoo...
National audienceThis paper addresses the issue of Out-Of-Vocabulary (OOV) word detection in Large V...
Utterance verification based on on-line garbage (OLG) models is often adopted as the benchmark metho...
This paper provides improved confidence assessment for detection of word-level speech recognition er...
This paper provides improved confidence assessment for detection of word-level speech recognition er...
This thesis develops and evaluates a set of utterance verification (UV) techniques as part of a larg...
Despite the significant advances in speech and language technologies speech recognition systems are ...
International audienceThis paper describes the design of an Out-Of- Vocabulary words (OOV) detector....
Spoken dialogue systems generally use one or two confidence thresholds during speech recognition. A ...
Abstract — This paper describes a fast and efficient method to detect out-of-vocabulary words and co...
Automatic Speech Recognition (ASR) systems continue to make errors during search when handling vario...
As with human-human interaction, spoken human-computer dialog will contain situations where there is...
In this paper we present a new application for confidence measures in spoken language processing. In...
A CALL system for oral proficiency is being developed in which constrained responses are elicited fr...
The approach proposed is an alternative to the tradi-tional architecture of Spoken Dialogue Systems ...
We propose a new confidence score for decoding and verification. Since the traditional log likelihoo...
National audienceThis paper addresses the issue of Out-Of-Vocabulary (OOV) word detection in Large V...
Utterance verification based on on-line garbage (OLG) models is often adopted as the benchmark metho...
This paper provides improved confidence assessment for detection of word-level speech recognition er...
This paper provides improved confidence assessment for detection of word-level speech recognition er...
This thesis develops and evaluates a set of utterance verification (UV) techniques as part of a larg...
Despite the significant advances in speech and language technologies speech recognition systems are ...
International audienceThis paper describes the design of an Out-Of- Vocabulary words (OOV) detector....
Spoken dialogue systems generally use one or two confidence thresholds during speech recognition. A ...
Abstract — This paper describes a fast and efficient method to detect out-of-vocabulary words and co...
Automatic Speech Recognition (ASR) systems continue to make errors during search when handling vario...
As with human-human interaction, spoken human-computer dialog will contain situations where there is...
In this paper we present a new application for confidence measures in spoken language processing. In...
A CALL system for oral proficiency is being developed in which constrained responses are elicited fr...
The approach proposed is an alternative to the tradi-tional architecture of Spoken Dialogue Systems ...
We propose a new confidence score for decoding and verification. Since the traditional log likelihoo...
National audienceThis paper addresses the issue of Out-Of-Vocabulary (OOV) word detection in Large V...