Nvidia Corporation

Nuance Communications, Inc.

Yifang Xu

Minwoo Park

John R Zedlewski

Pekka Janis

Zuoguan Wang

Gordon Grigor

Miguel Sainz

Davide Onofrio

Chia-Chih Chen

Vijay Chintalapudi

Carolina Parada

Mehdi Sajjadi Mohammadabadi

Xin Liu

Ozan Tonkal

Jan Nikolaus Fritsch

I-Kuei Chen

Mahesh Godavarti

Anurag Ratan Singh

Ivan A Sanchez Quijas

In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.

Real-time detection of lanes and boundaries by autonomous vehicles

A system and method configured for use in a text-to-speech (TTS) system is provided. Embodiments may include identifying, using one or more processors, a word or phrase as a named entity and identifying a language of origin associated with the named entity. Embodiments may further include transliterating the named entity to a script associated with the language of origin. If the TTS system is operating in the language of origin, embodiments may include passing the transliterated script to the TTS system. If the TTS system is not operating in the language of origin, embodiments may include generating a phoneme sequence in the language of origin using a grapheme to phoneme (G2P) converter.

Process for improving pronunciation of proper nouns foreign to a target language text-to-speech system

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San Jose, CA, United States of America

Yifang Xu