RNN-T Audio Decoding with Diagonal Switching for Parallel Inference

The patent segments the decoding process into multiple parallel decoding paths, where each path processes a specific coordinate increment pattern. This divides the complex RNN-T computation into manageable segments that can be executed in parallel, reducing overall computational complexity while maintaining recognition accuracy.

The patent introduces a new dimension by adding coordinate increment constraints in the audio frame and text label sequence dimensions. This transforms the traditional single-path decoding into a multi-dimensional parallel decoding structure, enabling faster computation without sacrificing accuracy.

By segmenting the decoding into multiple paths with different coordinate increment patterns, the patent reduces the memory footprint of each individual path. Each path processes a subset of the total computation, requiring less memory per path, while the parallel execution maintains overall accuracy.

The patent employs partial action by limiting each decoding path to specific coordinate increment patterns rather than exploring all possible paths. This partial exploration reduces memory requirements while still achieving accurate recognition through the combination of multiple constrained paths.

The patent segments the complete path exploration into multiple parallel decoding paths, each handling specific coordinate increment patterns. This segmentation enables simultaneous execution of multiple paths, dramatically increasing calculation speed while collectively covering the comprehensive search space.

By adding the dimension of parallel path execution with different coordinate increment constraints, the patent transforms sequential path exploration into concurrent multi-dimensional exploration. This enables both comprehensive coverage and high-speed calculation through parallel processing.