Phoneme Pitch Adjustment Using Binned Vectors for Expressive Speech
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Solution Overview
Problem
Existing text-to-speech systems lack the ability to finely tune the pitch of audio output, particularly at the phoneme level, which is crucial for nuanced emotional expression and semantic effects in applications like computer games.
Innovation Solution
A processor system that groups phoneme-level pitch values into bins and encodes them with vectors, using one-dimensional convolution layers and fully connected layers to predict and adjust pitch values, allowing for phoneme-by-phoneme control through graphical user interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If phoneme-level pitch control is implemented, then pitch precision is improved, but device complexity increases
Solution Approach 1:
The system segments pitch control into phoneme-level units, allowing independent control of pitch for each phoneme in the speech sequence. This segmentation enables precise pitch manipulation at the smallest meaningful linguistic unit, resolving the contradiction by achieving high pitch precision through granular control while managing complexity through modular phoneme-based processing
Solution Approach 2:
The system applies local quality by allowing different pitch values to be assigned to different phonemes based on their specific contextual requirements. Each phoneme can have its pitch independently adjusted to match emotional expression needs, semantic emphasis, or prosodic patterns, thereby achieving high pitch precision without requiring global pitch modification that would increase overall system complexity
2Adaptability or versatility
If phoneme-level pitch adjustment is enabled, then emotional expression is improved, but computational resources increase
Solution Approach 1:
The system performs preliminary action by pre-computing pitch values for each phoneme during the text-to-speech synthesis process, before audio generation. Pitch contours are calculated in advance based on the desired emotional expression and semantic context, allowing efficient runtime execution without excessive computational resource consumption during actual speech generation
Solution Approach 2:
The system applies partial action by adjusting pitch values only for phonemes that require emotional or semantic emphasis, rather than modifying every phoneme uniformly. This selective pitch modification approach achieves rich emotional expression while conserving computational resources by avoiding unnecessary pitch calculations for phonemes that do not require adjustment
Data Source
AI summary
An algorithm is provided for enabling game developers to create speech from text. The algorithm enables tailoring pitch of intermediate representations of phonemes on a phoneme-by-phoneme basis from the pitch output by a text-to-speech model.