{"id":673,"date":"2023-06-29T10:39:02","date_gmt":"2023-06-29T10:39:02","guid":{"rendered":"https:\/\/www.fidelsoftech.com\/case-studies\/?p=673"},"modified":"2025-08-13T12:41:53","modified_gmt":"2025-08-13T12:41:53","slug":"voice-data-processing-for-asr-engine","status":"publish","type":"post","link":"https:\/\/www.fidelsoftech.com\/case-studies\/voice-data-processing-for-asr-engine\/","title":{"rendered":"Voice Data Processing for ASR Engine and Extracting Value from Spoken Words – Case Study"},"content":{"rendered":"

[et_pb_section fb_built=”1″ fullwidth=”on” _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_fullwidth_image src=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2023\/06\/voice-data-processing-for-asr-engine-and-extracting-value-from-spoken-words-.jpg” alt=”Voice Data Processing for ASR Engine and Extracting Value from Spoken Words” _builder_version=”4.27.4″ _module_preset=”default” custom_margin=”||||false|false” global_colors_info=”{}”][\/et_pb_fullwidth_image][\/et_pb_section][et_pb_section fb_built=”1″ fullwidth=”on” _builder_version=”4.18.0″ _module_preset=”default” custom_margin=”2px||0px||false|false” global_colors_info=”{}”][et_pb_fullwidth_post_title meta=”off” featured_image=”off” _builder_version=”4.18.0″ _module_preset=”default” title_text_align=”left” custom_margin=”0px||||false|false” custom_padding=”30px||||false|false” global_colors_info=”{}”][\/et_pb_fullwidth_post_title][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.18.0″ _module_preset=”default” custom_padding=”25px||||false|false” global_colors_info=”{}”][et_pb_row module_class=”inner-page” _builder_version=”4.18.0″ _module_preset=”default” custom_padding=”0px||||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

About the client<\/h2>\n

The client, a prominent company, has transformed the shopping experience for all of us through the innovative use of cloud technology and Speech Recognition Engine (ASR).<\/p>\n

Requirements:<\/h3>\n

The client wanted to establish a process with minimum human intervention for transcribing the source audio data in multiple Indian and foreign languages.<\/p>\n

Challenges :<\/h3>\n

The client wanted us to develop a tool with an interface to process the source audio data and also to set up an automation process to perform quality assurance on the transcribed version. The greatest challenge was first to convert analog to digital signal processing, then to identify and classify speech and non-speech segments, and finally to preserve the important audio contents without any data loss for further text analysis.<\/p>\n

Solution Provided :<\/h3>\n

Fidel analyzed the requirements and identified key areas which play an important role in processing audio data and performs an analysis on transcribed audio contents.<\/p>\n

    \n
  1. Python<\/a> GUI which supports AI modules.<\/li>\n
  2. NLP<\/a> to identify language detection and classification on various target languages.<\/li>\n<\/ol>\n

    Based on this analysis, Fidel laid out the flow to achieve the audio signal processing with easy use of technology and programming languages like Python and its supported AI modules like NLP and NumPy.<\/p>\n

    \"analog<\/p>\n

    Analog to Digital Signal Processing:<\/strong><\/p>\n