Speech Synthesis Research Engineer ObEN, Inc.


STAGE 1: Phone Interview STAGE 2: In-person Interview at Idealab (we cover travel expenses for the day) STAGE 3: We require a sample project submission and a candidate proposal submission(To know more about what an ObEN candidate proposal is, click here) STAGE 4: Spend a day at our office and participate in all team activities.

Visualization and Interpretation of Latent Spaces for Controlling Expressive Speech Synthesis through Audio Analysis

arXiv.org Artificial Intelligence

The field of Text-to-Speech has experienced huge improvements last years benefiting from deep learning techniques. Producing realistic speech becomes possible now. As a consequence, the research on the control of the expressiveness, allowing to generate speech in different styles or manners, has attracted increasing attention lately. Systems able to control style have been developed and show impressive results. However the control parameters often consist of latent variables and remain complex to interpret. In this paper, we analyze and compare different latent spaces and obtain an interpretation of their influence on expressive speech. This will enable the possibility to build controllable speech synthesis systems with an understandable behaviour.

Bad Speech Synthesis Made Simple • /r/MachineLearning


Bad Speech Synthesis Made Simple (kastnerkyle.github.io) This is a little light on machine learning content besides the feature extraction and (brief) description of decision trees, but might be of interest for people looking at ways to synthesize sounds.

Issues in the Development of an Intelligent Human - Machine Interface

AAAI Conferences

Instead, they use statistical techniques to extract highly relevant portions of existing text. True summarisation would attempt to understand the contents of the document and restate it in a way appropriate to the discourse and the communication medium. As an example, consider the short Email given below: Hi Donald, Got your Email regarding the meeting on Friday with Warner Bros. rll be there.

Transition of Siri's Voice From Robotic to Human: Note the Difference - DZone AI


Being an iOS user, how many times do you talk to Siri in a day? If you are a keen observer, then you know that Siri's voice sounds much more like a human in iOS 11 than it has before. This is because Apple is digging deeper into the technology of artificial intelligence, machine learning, and deep learning to offer the best personal assistant experience to its users. From the introduction of Siri with the iPhone 4S to its continuation in iOS 11, this personal assistant has evolved to get closer to humans and establish good relations with them. To reply to voice commands of users, Siri uses speech synthesis combined with deep learning.