Speed Bumps for Authentic Listening Material
| Autor: | Marty Meinardi |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Linguistics and Language
Computer science business.industry First language Speech recognition Sample (material) Word count Snippet speed bumps computer.software_genre Language and Linguistics Computer Science Applications Education Computer software Stress (linguistics) audio Active listening Language proficiency Artificial intelligence business computer listening Natural language processing |
| Zdroj: | Articles |
| Popis: | This article investigates whether authentic native speaker (NS) to NS speech can be made available to the learner listener through the use of a novel slow-down tool. Results from various preliminary tests seem to indicate that the use of a slow-down algorithm in many cases, and in particular in samples with a higher speed rate and word count, leads to an improvement in subjects’ ability to perceive and understand what was being uttered in the samples. Tests revealed that even NS listeners, as opposed to non-native (NN) listeners, prefer to hear authentic NS speech which is either unscripted or is influenced by regional accent, at a slowed down speed. It also seems that ‘unexpected’ words (such as words with high contextual value, but which cannot be processed in a top-down fashion because of the size of the sound snippet) are initially not understood at the original speed of delivery, even in a scripted and carefully pronounced pedagogic sample. Samples containing chunks or formulaic sequences, however, appear to be easily understood at 100% by the majority of NS listeners due to the holistic processing of these language units. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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