Neural Network Speech Synthesis for Personalized Voice Delivery
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Solution Overview
Problem
Current systems for delivering voiced content lack the ability to dynamically alter speech patterns based on user behavior, experiences, and emotions, failing to provide personalized and contextually relevant voices.
Innovation Solution
A computer-implemented method that analyzes user profile data to recommend contextually applicable voices, transcribes voiced content into text, conditions a neural network with a voice sample to synthesize a waveform for artificial speech, and delivers the modified content, using advanced speech synthesis techniques like WaveNet or SampleRNN to mimic human-like voices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pre-recorded voice settings are used, then voice delivery is consistent and reliable, but adaptability to user preferences and behaviors is limited
Solution Approach 1:
The system dynamically adjusts voice characteristics by analyzing user profile data and behavior patterns in real-time, transitioning from static pre-recorded voices to adaptive synthesized voices that evolve with user preferences
Solution Approach 2:
The neural network modifies voice parameters such as pitch, tone, and speech patterns based on analyzed user data, enabling continuous adaptation without requiring re-recording of voice settings
2Adaptability or versatility
If neural network speech synthesis is used, then personalized voice delivery is achieved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary analysis of user profile data and pre-conditions the neural network with voice samples before actual speech generation is needed, reducing real-time processing requirements
Solution Approach 2:
The neural network creates synthesized copies of voice waveforms based on trained patterns, allowing rapid generation of personalized voices without requiring actual human recording for each instance
3Ease of operation
If contextually relevant voice recommendations are implemented, then user experience is enhanced, but data analysis requirements and system complexity increase
Solution Approach 1:
The system automatically analyzes user profile data and generates voice recommendations without requiring manual user input or configuration, enabling self-service personalization that reduces operational complexity
Data Source
AI summary
Systems, methods, and computer program products customizing and delivering contextually relevant, artificially synthesized, voiced content that is targeted toward the individual user behaviors, viewing habits, experiences and preferences of each individual user accessing the content of a content provider. A network accessible profile service collects and analyzes collected user profile data and recommends contextually applicable voices based on the user's profile data. As user input to access voiced content or triggers voiced content maintained by a content provider, the voiced content being delivered to the user is a modified version comprising artificially synthesized human speech mimicking the recommended voice and delivering the dialogue of the voiced content, in a manner that imitates the sounds and speech patterns of the recommended voice.