Shengxi Pan, Jia Liu, Jintao Jiang, Zuoying Wang, Dajin Lu
{"title":"一种基于多模型和集成决策方法的鲁棒语音识别算法","authors":"Shengxi Pan, Jia Liu, Jintao Jiang, Zuoying Wang, Dajin Lu","doi":"10.21437/ICSLP.1998-334","DOIUrl":null,"url":null,"abstract":"In this paper, a new robust speech recognition algorithm of multi-models and integrated decision(MMID) is proposed. A parallel MMID(PMMID) algorithm is developed. By using this new algorithm the advantages of different models can be integrated into one system. This algorithm uses different acoustic models at the same time based on DDBHMM (duration distribution based Hidden Markov Model)[2]. These different models include the channel-mismatch-correct(CMC) model, more-alternative-pronunciation model, tone and non-tone models of Chinese Mandarin speech, voice activity detection(VAD) model and state-skip model. The speech recognition accuracy of the multi-model system is better than that of single-model system in the adverse environments. The experimental results show that the error rate of the recognition system is 2.9% and reduced by 81% compared with the baseline system of the single-model.","PeriodicalId":117113,"journal":{"name":"5th International Conference on Spoken Language Processing (ICSLP 1998)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel robust speech recognition algorithm based on multi-models and integrated decision method\",\"authors\":\"Shengxi Pan, Jia Liu, Jintao Jiang, Zuoying Wang, Dajin Lu\",\"doi\":\"10.21437/ICSLP.1998-334\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new robust speech recognition algorithm of multi-models and integrated decision(MMID) is proposed. A parallel MMID(PMMID) algorithm is developed. By using this new algorithm the advantages of different models can be integrated into one system. This algorithm uses different acoustic models at the same time based on DDBHMM (duration distribution based Hidden Markov Model)[2]. These different models include the channel-mismatch-correct(CMC) model, more-alternative-pronunciation model, tone and non-tone models of Chinese Mandarin speech, voice activity detection(VAD) model and state-skip model. The speech recognition accuracy of the multi-model system is better than that of single-model system in the adverse environments. The experimental results show that the error rate of the recognition system is 2.9% and reduced by 81% compared with the baseline system of the single-model.\",\"PeriodicalId\":117113,\"journal\":{\"name\":\"5th International Conference on Spoken Language Processing (ICSLP 1998)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"5th International Conference on Spoken Language Processing (ICSLP 1998)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21437/ICSLP.1998-334\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"5th International Conference on Spoken Language Processing (ICSLP 1998)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21437/ICSLP.1998-334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel robust speech recognition algorithm based on multi-models and integrated decision method
In this paper, a new robust speech recognition algorithm of multi-models and integrated decision(MMID) is proposed. A parallel MMID(PMMID) algorithm is developed. By using this new algorithm the advantages of different models can be integrated into one system. This algorithm uses different acoustic models at the same time based on DDBHMM (duration distribution based Hidden Markov Model)[2]. These different models include the channel-mismatch-correct(CMC) model, more-alternative-pronunciation model, tone and non-tone models of Chinese Mandarin speech, voice activity detection(VAD) model and state-skip model. The speech recognition accuracy of the multi-model system is better than that of single-model system in the adverse environments. The experimental results show that the error rate of the recognition system is 2.9% and reduced by 81% compared with the baseline system of the single-model.