Language recognition using phonotactic-based shifted delta coefficients and multiple phone recognizers
نویسندگان
چکیده
A new language recognition technique based on the application of the philosophy of the Shifted Delta Coefficients (SDC) to phone log-likelihood ratio features (PLLR) is described. The new methodology allows the incorporation of long-span phonetic information at a frame-by-frame level while dealing with the temporal length of each phone unit. The proposed features are used to train an i-vector based system and tested on the Albayzin LRE 2012 dataset. The results show a relative improvement of 33.3% in Cavg in comparison with different state-of-the-art acoustic i-vector based systems. On the other hand, the integration of parallel phone ASR systems where each one is used to generate multiple PLLR coefficients which are stacked together and then projected into a reduced dimension are also presented. Finally, the paper shows how the incorporation of state information from the phone ASR contributes to provide additional improvements and how the fusion with the other acoustic and phonotactic systems provides an important improvement of 25.8% over the system presented during the competition.
منابع مشابه
Time-Frequency Cepstral Features and Combining Discriminative Training for Phonotactic Language Recognition
The performance of the phonotactic system for language recognition depends on the quality of the phone recognizers. To improve the performance of the recognizers, this paper investigates the use of new acoustic features and discriminative training techniques for phone recognizers. The commonly used features are static ceptral coefficients appended with their first and second order deltas. This ...
متن کاملLanguage Recognition Using Phone Lattices
This paper proposes a new phone lattice based method for automatic language recognition from speech data. By using phone lattices some approximations usually made by language identification (LID) systems relying on phonotactic constraints to simplify the training and decoding processes can be avoided. We demonstrate the use of phone lattices both in training and testing significantly improves t...
متن کاملLanguage recognition using phone latices
This paper proposes a new phone lattice based method for automatic language recognition from speech data. By using phone lattices some approximations usually made by language identification (LID) systems relying on phonotactic constraints to simplify the training and decoding processes can be avoided. We demonstrate the use of phone lattices both in training and testing significantly improves t...
متن کاملUsing cross-decoder co-occurrences of phone n-grams in SVM-based phonotactic language recognition
Most common approaches to phonotactic language recognition deal with several independent phone decoders. Decodings are processed and scored in a fully uncoupled way, their time alignment (and the information that may be extracted from it) being completely lost. Recently, we have presented a new approach to phonotactic language recognition which takes into account time alignment information, by ...
متن کاملImproving Language Recognition with Multilingual Phone Recognition and Speaker Adaptation Transforms
We investigate a variety of methods for improving language recognition accuracy based on techniques in speech recognition, and in some cases borrowed from speaker recognition. First, we look at the question of language-dependent versus language-independent phone recognition for phonotactic (PRLM) language recognizers, and find that language-independent recognizers give superior performance in b...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014