Voice-based Human-Machine Interaction Modeling for Automated Information Services

Maskeliūnas, Rytis; Ratkevicius, Kastytis; Rudzionis, Vytautas

doi:10.5755/j01.eee.110.4.300

Cited by 12 publications

(7 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The best keyword detection rate achieved in speaker-dependent search was 97 % (average detection rate was 93 %). These results correspond to the detection rate achieved by other search strategies in English speech [8] as well as in non-English speech [15].…”

Section: Discussionsupporting

confidence: 86%

Search for Keywords and Vocal Elements in Audio Recordings

Sigmund

2013

ElAEE

View full text Add to dashboard Cite

This paper deals with search for keywords and non-verbal vocal elements in audio recordings. An efficient detection of specific words or sounds embedded in continuous speech is based on isolated word recognition approaches. The mel-frequency cepstral coefficients and more combinations of predictive coefficients and autocorrelation coefficients were evaluated. A keyword or key sound slides along the stored speech and in each of its positions a distance (i.e., similarity) to the corresponding speech segment is computed. We found an efficient distance measure for non-verbal sound search. The average detection rates achieved 93 percent in keyword search and 74 percent in non-verbal sound search. A system developed for automatic search in audio files is presented.

show abstract

Section: Discussionsupporting

confidence: 86%

Search for Keywords and Vocal Elements in Audio Recordings

Sigmund

2013

ElAEE

View full text Add to dashboard Cite

show abstract

“…It has been shown that such mapping allows the achievement of acceptable recognition accuracy for a large group of applications. The Spanish speech recognition engine was used since our earlier investigations showed that Spanish has the closest acoustic similarity to Lithuanian among commercially available recognizers [6].…”

Section: Recognition Experiments Using Adapted Foreign Language Enginementioning

confidence: 99%

Comparative Analysis of Adapted Foreign Language and Native Lithuanian Speech Recognizers for Voice User Interface

Rudzionis

Raškinis

Maskeliūnas

et al. 2013

ElAEE

Self Cite

View full text Add to dashboard Cite

Paper presents research results obtained when building a speaker independent hybrid speech recognizer. This recognizer will be integrated as a phrase recognizer in a medical-pharmaceutical information system. The hybrid speech recognizer consists of two recognition components: an adapted commercial Microsoft Spanish speech recognizer and a locally developed hidden Markov models based recognizer implementing Lithuanian acoustic models. Efficiency of both recognition components was evaluated on multiple speaker independent speech recognition tasks. The average accuracy of Lithuanian recognizer was higher reaching 0.6% phrase error rate for user requests in medical-pharmaceutical domain. The adapted commercial Spanish speech recognizer showed the ability to improve the accuracy of Lithuanian recognizer in the worst recognition scenarios. These results proved the hypothesis formulated when proposing the basic idea of hybrid recognition approach: recognition errors from different recognizers built using various techniques are not strongly correlated. This fact could be exploited for improved overall speech recognition accuracy.

show abstract

“…The experiments were carried out using the Slovenian 1000 FDB SpeechDat(II) database, which is part of the SpeechDat family with more than 50 different languages available. A database of this type can be used to develop voice-driven services [13] and various applications. It was recorded over a fixed telephone with 1,000 different speakers within the set.…”

Section: Speech Databasementioning

confidence: 99%