Abstract: Techniques discussed herein relate to reducing latency in a Text-To-Speech processing pipeline. A request may be received requesting a speech waveform corresponding to input text provided in the request. The input text may be processed using a set of text preprocessing operations to generate a set of sound units. The set of sound units may be provided to an acoustic model to generate sound frequency data which may be divided into a number of smaller sound frequency data segments corresponding to the number of available computing threads. Each thread may be configured to provide a respective sound frequency data segment to a neural network as input to generate a plurality of speech waveforms. The plurality of speech waveforms may be combined to generate the speech waveform requested. The combined speech waveform may be provided in response to the request.

Abstract: The present invention discloses robotic process automation (RPA) of supply chain management (SCM) operations. In example embodiments the invention discloses RPA method and systems for supply chain management. The RPA systems include IOT devices and server as part of a sub network for secured communication relating to SCM operations like procurement operations. The system and method of the present invention utilizes AI based processing logic using a bot for automation of SCM operations thereby reducing the processing times and increasing efficiency.

Abstract: The present invention discloses robotic process automation (RPA) of supply chain management (SCM) operations. In example embodiments the invention discloses RPA method and systems for supply chain management. The RPA systems include IOT devices and server as part of a sub network for secured communication relating to SCM operations like procurement operations. The system and method of the present invention utilizes AI based processing logic using a bot for automation of SCM operations thereby reducing the processing times and increasing efficiency.