نتایج جستجو برای: تبدیل mllr
تعداد نتایج: 35597 فیلتر نتایج به سال:
This paper presents an online/sequential linear regression adaptation framework for hidden Markov model (HMM) based speech recognition. Our attempt is to sequentially improve speaker-independent speech recognition system to handle the nonstationary environments via the linear regression adaptation of HMMs. A quasi-Bayes linear regression (QBLR) algorithm is developed to execute the sequential a...
The current speech interfaces in many military applications may be adequate for native speakers. However, the recognition rate drops quite a lot for non-native speakers (people with foreign accents). This is mainly because the nonnative speakers have large temporal and intra-phoneme variations when they pronounce the same words. This problem is also complicated by the presence of large environm...
To make full use of a small development data set to build a robust dialectal Chinese speech recognizer from a standard Chinese speech recognizer (based on Chinese Initial/Final, IF), a novel, simple but effective acoustic modeling method, named state-dependent phoneme-based model merging (SDPBMM), is proposed and evaluated, where a shared-state of standard tri-IF is merged with a state of diale...
اخیراً دادهها در سازمانها به دارایی ارزشمندی تبدیل شدهاند و حاکمیت داده یکی از اولویتهای شده است. بررسی مطالعات پیشین نشان میدهد که سنجش استقرار بهصورت کیفی انجام میشود نمیتوانند بر اساس این نوع برنامهای را برای بهبود وضعیت خود تعیین کنند. هدف پژوهش، ارائه روشی کمّی سطح یک سازمان متعاقباً برنامهریزی موجود با توجه ماهیت عوامل تأثیرگذار میزان مفاهیم فازی مدلسازی تحلیل استفاده است؛ همچنین ...
Inter-speaker variation can be coped rather well in speech recognition by speaker adaptation techniques such as MLLR and MAP. However, when dealing with speech other than reading style, such as conversational speech, emotional speech and so on, current recognition systems cannot achieve a satisfactory performance even after speaker adaptation. In view of this situation, two-level adaptation met...
In this paper we describe a novel approach to address the issue of different sampling frequencies in speech recognition. In general, when a recognition task needs a different sampling frequency from that of the reference system, it is customary to retrain the system for the new sampling rate. To circumvent the tedious training process, we propose a new approach termed Sampling Rate Transformati...
The speaker-dependent HMM-based recognizers gives lower word error rates in comparison with the corresponding speaker-independent recognizers. The aim of speaker adaptation techniques is to enhance the speakerindependent acoustic models to bring their recognition accuracy as close as possible to the one obtained with speaker-dependent models. In this paper, we propose a method using test and tr...
To achieve natural high quality synthesised speech in HMMbased speech synthesis, the effective modelling of complex acoustic and linguistic contexts is critical. Traditional approaches use context-dependent HMMs with decision tree based parameter clustering to model the full combination of contexts. However, weak contexts, such as word-level emphasis in neutral speech, are difficult to capture ...
The current speech interfaces in many military applications may be adequate for native speakers. However, the recognition rate drops quite a lot for non-native speakers (people with foreign accents). This is mainly because the nonnative speakers have large temporal and intra-phoneme variations when they pronounce the same words. This problem is also complicated by the presence of large environm...
This paper describes our German and English Speechto-Text (STT) systems for the 2016 IWSLT evaluation campaign. The campaign focuses on the transcription of unsegmented TED talks. Our setup includes systems using both the Janus and Kaldi frameworks. We combined the outputs using both ROVER [1] and confusion network combination (CNC) [2] to archieve a good overall performance. The individual sub...
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