Google Inc.

Beijing Didi Infinity Technology and Development Co., Ltd.

Yang Yu

Ignacio Lopez Moreno

Quan Wang

Li Wan

Prashant Sridhar

Zhiwei Qin

Jieping Ye

Qingyang Li

Yiping Meng

Wenjie Shang

A system and method of determining a policy to prevent fading drivers is described. The system and method creates virtual trajectories of incentives such as coupons offered to drivers in a transportation hailing system and corresponding states of drivers in response to the incentives. A joint policy simulator is created from an incentive policy, a confounding incentive policy, and an incentive object policy to generate the simulated actions of drivers in response to different incentives. The rewards of the simulated actions of the drivers is determined by a discriminator. The incentive policy for preventing fading drivers is optimized by reinforcement learning based on the virtual trajectories generated by the joint policy simulator and discriminator.

Reinforcement learning method for driver incentives: generative adversarial network for driver-system interactions

Methods and systems for training and/or using a language selection model for use in determining a particular language of a spoken utterance captured in audio data. Features of the audio data can be processed using the trained language selection model to generate a predicted probability for each of N different languages, and a particular language selected based on the generated probabilities. Speech recognition results for the particular language can be utilized responsive to selecting the particular language of the spoken utterance. Many implementations are directed to training the language selection model utilizing tuple losses in lieu of traditional cross-entropy losses. Training the language selection model utilizing the tuple losses can result in more efficient training and/or can result in a more accurate and/or robust model&#x2014;thereby mitigating erroneous language selections for spoken utterances.

Training and/or using a language selection model for automatically determining language for speech recognition of spoken utterance

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Yang Yu