Abstract: A method for a user device, including receiving a first acoustic input of a user speaking a wake-up word in the target language; providing a first acoustic feature derived from the first acoustic input to an acoustic model stored on the user device to obtain a first sequence of speech units corresponding to the wake-up word spoken by the user in the target language, the acoustic model trained on a corpus of training data in a source language different than the target language; receiving a second acoustic input including the wake-up word in the target language; providing a second acoustic feature derived from the second acoustic input to the acoustic model to obtain a second sequence of speech units corresponding to the wake-up word in the target language; and comparing the first and second sequences of speech units to recognize the wake-up word in the target language.

Abstract: A user device configured to perform wake-up word detection in a target language.

Abstract: A user device configured to perform wake-up word detection in a target language.

Abstract: Methods and an apparatus for performing feature extraction on speech in a microphone signal with embedded noise processing to reduce the amount of processing are provided. In embodiments, feature extraction and the noise estimate use an output of the same Fourier Transform, such that the noise filtering of the speech is embedded with the feature extraction of the speech.

Abstract: Methods and an apparatus for performing feature extraction on speech in a microphone signal with embedded noise processing to reduce the amount of processing are provided. In embodiments, feature extraction and the noise estimate use an output of the same Fourier Transform, such that the noise filtering of the speech is embedded with the feature extraction of the speech.

Abstract: A user device configured to perform wake-up word detection in a target language.

Abstract: Techniques disclosed herein include systems and methods of automated speech recognition (ASR) for voice destination entry (VDE) include open voice searching (natural language searching) of destinations. A first part uses a server-based automated speech recognizer. The second part is client-based automatic speech recognition (ASR) processing. Thus, techniques include a hybrid VDE solution that provides users with an accurate and flexible way to use speech recognition technologies. A server-based speech recognizer executes the open-search task, while a client-based recognizer refines the results from the server to deliver an optimized result. This system and method significantly improves recognition accuracy for dictation engine based POI search of Chinese Mandarin input and input from other languages. Moreover, the methods herein largely improve the user experience by allowing users to say a partial POI name, and abbreviation, or even say a POI name in a reversed word order.