Name
Abstract | ||
|---|---|---|
ABSTRACT In the past few years, the Large Vocabulary Conversational Speech Recognition (LVCSR) community has attempted to address the problem of speech recognition on languages other than English Work on the CallHome Corpora has veri ed that current technology is largely language independent, and that the dominant factor with regards to performance on a certain language is the amount of training data available ([1]) This brings forth the question of what is the appro - priate course of action when we need to quickly bring a rec - ognizer up in a new language, were little or no training is available This is exactly the question we will address in this paper We will assume that, while only a couple of hours of transcribed data is available, much more untranscribed data can be found, and we will explore ways to utilize it |
Year | Venue | Keywords |
|---|---|---|
1998 | ICSLP | automatic speech recognition,speech recognition |
Field | DocType | Citations |
Speech corpus,Speech synthesis,Speech analytics,Audio mining,Computer science,Speech recognition,Speaker recognition,Natural language processing,Artificial intelligence,Vocabulary,Speech technology,Acoustic model | Conference | 25 |
PageRank | References | Authors |
3.82 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| George Zavaliagkos | 1 | 200 | 50.01 |
| Gte Internetworking | 2 | 25 | 3.82 |
| Thomas Colthurst | 3 | 78 | 7.71 |