Current and experimental applications of speech technology for telecom services in Europe

Johnston, Denis; Sorin, Christel; Gagnoulet, C.; Charpentier, F.; Canavesio, F.; Lochschmidt, B.; Álvarez, Jorge; Cortázar, Ismael; Tapias, Daniel; Crespo, C.; Azevedo, J.; Chaves, R. M.

doi:10.1016/s0167-6393(97)00050-2

Cited by 9 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, all ASR systems aim to automatically extract the string of spoken words from the given input speech signals as illustrated in Figure 1 During the past decade, research in automatic speech recognition has produced increasingly better results for a wide range of tasks. At the same time, the evolution of telephone and the widespread use of telephones are urging telephony service providers to apply speech technology [2]. Application such as mobile banking system where person authentication can be granted based on the digits he pronounces over a phone, voice dialing and so on.…”

Section: Introductionmentioning

confidence: 99%

Hindi Number Recognition using GMM

RaiGoyal¹,

Koolagudi²

2013

IJCA

View full text Add to dashboard Cite

This paper aims at designing and implementation of Hindi number recognition system using the microphone and mobile recorded speech. Spectral features known to represent phonetic information are used as the features to characterize different Hindi digits. Gaussian mixture models (GMM) are used to develop the digit recognition system. This paper focuses on the ten basic Hindi digits where '0' is pronounced as 'shunya' to '9' is pronounced as 'no'. Data has been collected separately from male, female and child speakers using microphone and mobile phone device. The experimental results show that the overall accuracy of digit recognition is 98.9\% in the case of microphone recorded speech and 96.4\% in the case of mobile phone recorded speech. Keywords-Gaussian mixture models (GMM), Mel frequency cepstral coefficients (MFCC), Hindi digit microphone database (HDMD), Hindi digit telephonic database (HDTD).

show abstract

Section: Introductionmentioning

confidence: 99%

Hindi Number Recognition using GMM

RaiGoyal¹,

Koolagudi²

2013

IJCA

View full text Add to dashboard Cite

show abstract

“…Most of these systems have been developed for use over the telephone network with the goal of replacing completely or assisting a human operator [5]. A key aspect of them is that they operate in a rather restricted domain of discourse (e.g.…”

Section: Introductionmentioning

confidence: 99%

Tessa, a system to aid communication with deaf people

Cox

Lincoln

Tryggvason

et al. 2002

Proceedings of the Fifth International ACM Conference on Assistive Technologies

124

View full text Add to dashboard Cite

TESSA is an experimental system that aims to aid transactions between a deaf person and a clerk in a Post Office by translating the clerk's speech to sign language. A speech recogniser recognises speech from the clerk and the system then synthesizes the appropriate sequence of signs in British Sign language (BSL) using a speciallydeveloped avatar. By using a phrase lookup approach to language translation, which is appropriate for the highly constrained discourse in a Post Office, we were able to build a working system that we could evaluate. We summarise the results of this evaluation (undertaken by deaf users and Post office clerks), and discuss how the findings from the evaluation are being used in the development of an improved system.

show abstract