Voice Technology Specialist

5 days ago

Kota, Rajasthan, India beBeeArtificial Full time ₹ 1,00,00,000 - ₹ 2,00,00,000

We are seeking a highly skilled Voice Technology Specialist to join our team.

This role involves designing, training, and refining AI models for voice synthesis, speech recognition, and voice transformation.

The ideal candidate will have a proven track record of:

  • Creating human-like voice synthesis with text-to-speech models that maintain the unique style of voice actors across multiple languages.
  • Implementing real-time processing solutions that reduce inference time to under 1 second, enhancing user interaction and experience.
  • Managing large-scale datasets for voice cloning projects, ensuring high performance and reliability while supporting multilingual transcriptions.
Key Responsibilities
  • Design and fine-tune deep learning models for voice synthesis (e.g., TTS, voice cloning).
  • Implement and optimize neural network architectures such as Tacotron, FastSpeech, WaveNet, or similar.
  • Collect, preprocess, and augment speech datasets.
  • Collaborate with product and engineering teams to integrate voice models into production systems.
  • Perform evaluation and quality assurance of voice model outputs.
  • Research and stay current on advancements in speech processing, audio generation, and machine learning.
Required Skills
  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field.
  • Strong experience with Python and machine learning libraries (e.g., PyTorch, TensorFlow).
  • Hands-on experience with speech/audio processing and relevant toolkits (e.g., Librosa, ESPnet, Kaldi).
  • Familiarity with voice model architectures (TTS, ASR, vocoders).
  • Understanding of deep learning concepts and model training processes.
Preferred Qualifications
  • Experience with deploying models to real-time applications or mobile devices.
  • Knowledge of data labeling, voice dataset creation, and noise handling techniques.
  • Experience with cloud-based AI/ML infrastructure (e.g., AWS, GCP).
  • Contributions to open-source projects or published papers in speech/voice-related domains.

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