This type of engineers are well versed in classical speech processing methodologies like hidden Markov models (HMMs), Gaussian mixture models (GMMs), Artificial neural networks (ANNs), Language modeling, etc.
Working on the creation of multilingual on-device voice recognition systems is what a speech engineer does.
You will be working on issues related to speech-focused research, such as speech improvement, voice analysis, and synthesis, in addition to ASR.
Building a whole pipeline for voice recognition, from data preparation to deployment on edge devices, will be your responsibility.
Another important aspect of your daily existence will be reading, putting into practise, and enhancing baselines mentioned in top research publications.
The creation of an ASR engine employing the ESPNET, FairSeq, Athena, or Deep Speech frameworks with PyTorch, Tensorflow, or Kaldi.
Working on speech technologies such as speaker separation, multilingual ASR, contextual iassing, text to speech, and voice biometrics.
Assist in defining the additional technology needed for speech technology and in designing the integration of that technology.
Improve the model’s ability to adapt to various domains and channels.
For technologies like text-to-speech, speaker recognition, and automatic voice recognition, benchmark and validate predictive speech models.
Sources for various speech datasets, data collecting, and the creation of new ones as required.
Incorporate a wide range of machine learning and statistical methods, including regression, classification, and deep learning.
Utilize cutting-edge cloud platforms like GCP to build pipelines for automated training and testing.
Knowledge of machine learning (ML), practical expertise with deep learning (DL) methods like CNN, RNN, LSTM, etc., and familiarity with speech recognition frameworks like ESPNET, FairSeq, Athena, and Deep Speech.
Good to have: Grapheme to Phonemes, DL-based and Non-DL-based.
Far-field speech technology using beamforming techniques for speech recognition and voice biometrics.
Amazon
Flipkart
Myntra etc
Numerous internship opportunities are available with tech behemoths like Google an Microsoft. Try to secure one for yourself because it will provide you practical experience, stand out on your CV, and, if you do well, may even lead to a full-time position.
Rohit Prasad
AI and machine learning jobs have jumped by almost 75 percent over the past four years and are poised to keep growing. Pursuing a machine learning job is a solid choice for a high-paying career that will be in demand for decades.
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