Speech Capture, Transcription and Analysis App

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Presentation transcript:

Speech Capture, Transcription and Analysis App August 2018

NTT DATA Vision NTT DATA is a Global IT Innovator. We realizing the dreams of our clients around the world through long-term relationships.     We Put Our Clients First: We enable out clients to reach their highest goals and aspirations. We Value Foresight: We create evolving ecosystems through advanced technology. With speed and foresight, we anticipate and address the challenges that lay ahead. We Value Teamwork: We enhance our creativity through the respect and encouragement of diversity at every level of our company.

Speech Capture, Transcription & Analysis Speech capture, transcription and analysis app is an application that will help business analysts capture content of their interviews with potential clients and transform those conversation into searchable text and business insights. In modern, large scale industrial and financial institutions significant portion of IT services is transferred from in-house operations to organizations like NTT DATA which subsequently provide maintenance and support of the software apps as well as the development of new applications. Process of modifying applications or creating brand new applications requires collection of business and other requirements. Application that will be developed in this project will to a great degree improve the quality of this requirements gathering process, by replacing taking notes by hand or simple video recording by a more meaningful sound recording and transcription.

Deliverables Students will design and build a web application that will allow the interviewer to capture his or her conversation with client’s subject matter experts (SMEs). The application will transcribe captured conversation into text, extract key phrases, entities & sentiment. Captured text will be searchable. Application will also organize various parts of the interviews by topics for easier discovery and knowledge management. We will make an attempt to analyze the captured text and provide indicators or annotations for various parts of the conversation.

Software Frameworks We will build this application using various COTS components. User interface which selects documents for translation could be on a local machine or in the Cloud. The core of the application will reside in the Cloud. Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions. With Amazon Lex, the same deep learning technologies that power Amazon Alexa are now available to any developer, enabling you to quickly and easily build s Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to their applications. Using the Amazon Transcribe API, you can analyze audio files stored in Amazon S3 and have the service return a text file of the transcribed speech.ophisticated, natural language, conversational bots (“chatbots”).

Skill Sets For work in the Cloud Python or Java programming language and some Linux scripting are needed. Some familiarity with AWS Amazon Cloud. Some familiarity with machine learning concepts. By the end of the project students will acquire working knowledge of AWS Lex and AWS Transcribe and several other AWS services. By the end of the project students will become familiar with most important concepts in Machine Learning. Students will also become skillful Python developers.

Communications and Results Students implementing the project should have one or several meetings every week discussing progress and implementation details. There will be one mandatory weekly meeting with project sponsor. All work, including all architectural documents and functioning code should be delivered at the end of the project to NTT DATA.