Name
Abstract | ||
|---|---|---|
During the last years, language resources for speech recognition have been collected for many languages and specifically, for global languages. One of the characteristics of global languages is their wide geographical dispersion, and consequently, their wide phonetic, lexical, and semantic dialectal variability. Even if the collected data is huge, it is difficult to represent dialectal variants accurately. This paper deals with multidialectal acoustic modeling for Spanish. The goal is to create a set of multidialectal acoustic models that represents the sounds of the Spanish language as spoken in Latin America and Spain. A comparative study of different methods for combining data between dialects is presented. The developed approaches are based on decision tree clustering algorithms. They differ on whether a multidialectal phone set is defined, and in the decision tree structure applied. Besides, a common overall phonetic transcription for all dialects is proposed. This transcription can be used in combination with all the proposed acoustic modeling approaches. Overall transcription combined with approaches based on defining a multidialectal phone set leads to a full dialect-independent recognizer, capable to recognize any dialect even with a total absence of training data from such dialect. Multidialectal systems are evaluated over data collected in five different countries: Spain, Colombia, Venezuela, Argentina and Mexico. The best results given by multidialectal systems show a relative improvement of 13% over the results obtained with monodialectal systems. Experiments with dialect-independent systems have been conducted to recognize speech from Chile, a dialect not seen in the training process. The recognition results obtained for this dialect are similar to the ones obtained for other dialects. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.specom.2008.08.003 | Speech Communication |
Keywords | Field | DocType |
multidialectal system,spanish language,multidialectal phone set,multidialectal acoustic model,overall transcription,spanish acoustic modeling,multidialectal spanish acoustic modeling,common overall phonetic transcription,proposed acoustic modeling approach,training data,speech recognition,global language,multidialectal acoustic modeling,multidialectal asr system,spanish dialects,dialect-independent asr system,data collection,decision tree,physical sciences | Decision tree,Audio signal,Speech processing,Phonetic transcription,Computer science,Phonetics,Speech recognition,Phone,Tree structure,Cluster analysis | Journal |
Volume | Issue | ISSN |
51 | 3 | Speech Communication |
Citations | PageRank | References |
4 | 0.49 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mónica Caballero | 1 | 6 | 1.23 |
| Asunción Moreno | 2 | 399 | 44.97 |
| Albino Nogueiras | 3 | 139 | 15.27 |