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A repository belonging to a paper (INSERT), implementing speaker count estimation using a CRNN, based on a dataset with single-speaker fragments only

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AuckeBos/Speaker-count-estimation-based-on-an-artificially-generated-data-set

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Speaker count estimation based on an artificially generated data set

This repo is created for the exam project of the course Automatic Speach Recognition ( LET-REMA-LCEX10). The goal, its structure, and its results are elaborated upon in the corresponding paper.

In short: the goal of the project is to try to train a Recurrent Neural Network on an artifically created dataset of concurrent speakers. We tested performance on different levels.

Installation

  • Install Poetry: pip install poetry
  • Run poetry install to install the virtual environment
  • Run poetry python main.py to run the project. Choose which tasks to run by changing the variable at the top of the file.
  • [Optional] Run poetry shell to enter the virtual environment

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A repository belonging to a paper (INSERT), implementing speaker count estimation using a CRNN, based on a dataset with single-speaker fragments only

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