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similarities between posteriorgrams. In addition to deriving the lower-bound estimate, we show how it can be efficiently used in an admissible K nearest neighbor (KNN) search for spotting matching sequences. We quantify the amount of computational savings achieved by performing a set of unsupervised spoken keyword spotting
, pattern recognition) to detect such critical documents. To address difficult or ambiguous instances, we supplement the text classifier with an automated keyword search. That is, we extract, in an automated fashion, discriminative terms (i.e., keywords) from the training set and match them against documents during the
characters, even on syllabic alphabets like Amharic. In addition, we report improvements in word error rate from rescoring lattices and evaluate keyword search performance on several languages.
is proposed to combine VTLP and SFM as complementary approaches. Experiments are conducted on Assamese and Haitian Creole, two development languages of the IARPA Babel program, and improved performance on automatic speech recognition (ASR) and keyword search (KWS) is reported.
In particular for “low resource” Keyword Search (KWS) and Speech-to-Text (STT) tasks, more untranscribed test data may be available than training data. Several approaches have been proposed to make this data useful during system development, even when initial systems have Word Error Rates (WER) above 70
This paper investigates the effectiveness of knowledge distillation in the context of multilingual models. We show that with knowledge distillation, Long Short-Term Memory(LSTM) models can be used to train standard feed-forward Deep Neural Network (DNN) models for a variety of low-resource languages. We then examine how the agreement between the teacher's best labels and the original labels affects...
The recurrent neural network language model (RNNLM) is a discriminative, non-Markovian model that can capture long-span word history in natural language. It has been proved to be successful in automatic speech recognition and machine translation. In this work, we applied RNNLM to the n-best rescoring stage of the state-of-the-art BBN Byblos OCR (optical character recognition) system for handwriting...
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