Audio transcription with authors breakdown and multi-modular verification
67 USD We are looking for a Python developer with experience working with API for speech recognition and machine learning to upgrade the existing transcription script.The project aims to create an advanced system that optimizes the process of transcription of audio files with breakdown on the authors of the conversation.The system will use several speaking recognition services (Google Cloud Speech-to-Text, Whisper, Microsoft Azure Speech), as well as machine learning to improve the quality and accuracy of transcription.The main objectives of the project:
1 .** Modification of the existing script:**
- Integrate the API of various speaking recognition services: Google Cloud Speech-to-Text, Whisper, and Microsoft Azure Speech to improve the quality of recognition.(There is a whisper, other models are needed)
Develop the logic of choosing the best service for a specific audio fragment based on quality and value.2nd*Development of the mechanism of long fragments:**
Automatic breakdown of the audio into long and short fragments.(it is already there)
Processing long fragments using the advanced capabilities of selected recognition services.Three**GPT integration and optimization for context analysis:**
Integration of the GPT model to verify and improve the quality of transcription by analyzing the context of conversation.(it isExamples for the test)
Development of processing algorithms returned by the GPT model of conclusions for the correction and supplementation of the received transcription.4 .* Testing and validation of the system:**
A comprehensive testing of the system on different types of audio materials.Analysis of the accuracy, speed and cost of transcriptions obtained using different services and algorithms.and 5.* Developing the user interface:**
Create a simple and intuitively understandable interface to run the script and view the results.( to be discussed )
Requirements for qualification:
Knowledge of Python programming language and experience of at least 3 years.Experience with Speech Recognition API (Google Cloud Speech-to-Text, Whisper, Microsoft Azure Speech) and other cloud services.Experience in machine learning, especially with natural language processing models such as GPT-3.Understanding the principles of processing and analysis of audio data.Capacity to analyze and solve complex tasks.Attention to the details and a desire for a high quality of the work.## The expected results:
At the end of the project, the developer must provide a finished system capable of:
Automatically break the audio into fragments and determine the authors of the speech.Optimally allocate fragments between different recognition services to get the best results.Use GPT to analyze context and improve transcription accuracy.Reporting the quality and cost of the transcription process.Budget and deadlines:
The budget of the project and the deadlines for its implementation will be agreed with the developer after a detailed discussion of the work volume and the assessment of the time for the implementation of all functions.## The selection process:
1 .Examination of portfolio and experience of working with similar tasks.2ndInterview to discuss the details of the project and the possibility of implementation of the intended.ThreeDiscussing the conditions of cooperation and signing the contract.
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