A language score based output selection methodfor multilingual speech recognition
Table 1: Audio datasets
['[BOLD] Set', '[BOLD] Language', '[BOLD] Corpus', '[BOLD] Hours', '[BOLD] Speakers', '[BOLD] Sentences', '[BOLD] Foreign words', '[BOLD] Style']
4 testing sets were used to evaluate for Vietnamese performance. They were named Reading-test, Conversation-test, YouTube-test, and VLSP2018. For English evaluation, testing sets were Test-clean and Test-other [librispeech]. Those sets were randomly selected from the same raw data at the beginning to construct training, evaluation, and test sets, excepting the YouTube-test and VLSP2018. The YouTube-test was randomly collected from YouTube. It includes teenage conversations and technique talks with a lot of noises like music, non-human sounds. This was the most challenging test set since it not only is a noisy speech but also contains many foreign words. The percentage of foreign words in the vocabulary of this set is up to 23% with 939 unique words, and most of them are common English words and property names. The accuracy of foreign words recognition will be evaluated only for this set because the ratio in others is not significant. VLSP2018 was developed by research teams involved in Vietnamese language and speech processing [vlsp2018]. All audio files were saved to wave format with sample rate of 16kHz and analog/digital conversion precision of 16 bits.