AL-Lisaniyyat
Volume 22, Numéro 2, Pages 1-5
2016-05-30
Authors : G. Elfeky Mohamed . Moreno Pedro . Soto Victor .
Research has shown that automatic speech recognition (ASR) performance typically decreases when evaluated on a dialectal variation of the same language that was not used for training its models. Similarly, models simultaneously trained on a group of dialects tend to underperform when compared to dialect-specific models. When trying to decide which dialect-specific model (recognizer) to use to decode an utterance (e.g., a voice search query), possible strategies include automatically detecting the spoken dialect or following the user's language preferences as set in his/her cell phone. In this paper, we observe that user's voice search queries are usually directed to a dialect-specific recognizer that does not match the user's current location, and present a study that shows that automatically selecting the recognizer based on the user's geographical location helps improve the user experience.
multi-dialectical languages- Speech recognition- Voice search
فيجل زهرة
.
كتفي عزوز
.
ص 295-319.
Bougherira Naima
.
pages 9-55.
Lahiouel Azza
.
pages 38-49.
Wahiba Harem
.
pages 140-162.
Seddiki Safia
.
Tidjani Chemseddine
.
Zergoune Mohamed
.
pages 347-359.