Name
Abstract | ||
|---|---|---|
utomatic speech recognition (ASR) technology has matured over the past few decades and has made significant impacts in a variety of fields, from assistive technologies to commercial products. However, ASR system development is a resource intensive activity and requires language resources in the form of text annotated audio recordings and pronunciation dictionaries. Unfortunately, many languages found in the developing world fall into the resource-scarce category and due to this resource scarcity the deployment of ASR systems in the developing world is severely inhibited. One approach to assist with resource-scarce ASR system development, is to select "useful" training samples which could reduce the resources needed to collect new corpora. In this work, we propose a new data selection framework which can be used to design a speech recognition corpus. We show for limited data sets, independent of language and bandwidth, the most effective strategy for data selection is frequency-matched selection and that the widely-used maximum entropy methods generally produced the least promising results. In our model, the frequency-matched selection method corresponds to a logarithmic relationship between accuracy and corpus size; we also investigated other model relationships, and found that a hyperbolic relationship (as suggested from simple asymptotic arguments in learning theory) may lead to somewhat better performance under certain conditions. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s10579-014-9285-0 | Language Resources and Evaluation |
Keywords | Field | DocType |
Resource-scarce,Data selection,Corpus design,Speech recognition | Pronunciation,Data set,Software deployment,Scarcity,Data selection,Computer science,Learning theory,Speech recognition,Bandwidth (signal processing),Natural language processing,Artificial intelligence,Principle of maximum entropy | Journal |
Volume | Issue | ISSN |
49 | 2 | 1574-020X |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Neil Taylor Kleynhans | 1 | 0 | 0.68 |
| Etienne Barnard | 2 | 438 | 57.85 |