Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Training Neural TTS - Generate Realistic Voices in Production training are: Proficiency in PyTorch/TensorFlow, advanced deep learning (Transformers, GANs), audio processing (librosa, torchaudio). A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Neural TTS - Generate Realistic Voices in Production training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Training Neural TTS - Generate Realistic Voices ... | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Training Neural TTS - Generate Realistic Voices in Production training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Training Neural TTS - Generate Realistic Voices in Production training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Training Neural TTS - Generate Realistic Voices in Production training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training objectives

Master Neural TTS architectures for ultra-realistic professional voices

Develop and train certified TTS models adapted to the enterprise

Optimize neural speech synthesis for minimal latency in production

Implement Neural TTS pipelines with fine-tuning and transfer learning

Deploy scalable Neural TTS applications connected to voice APIs

Evaluate and audit TTS model performance in a professional context

Design ethical Neural TTS solutions compliant with GDPR

Training program

Module 1Neural TTS Architectures: Tacotron and WaveGlow (models, datasets, preprocessing)

Dive into advanced architectures like Tacotron 2 and WaveGlow, preparation of high-quality audio datasets with tools like Montreal Forced Aligner and librosa, setting up a PyTorch environment for Neural TTS, practical exercises on spectrograms and text-to-speech alignment, creation of a first baseline model with subjective MOS evaluation, immediate feedback to accelerate your professional skills.

Module 2Neural TTS Training: GPU Optimization and Hyperparameters (loss functions, schedulers)

Launch training of Neural TTS models on GPU clusters via torchaudio and ESPnet, hyperparameter tuning with Optuna to minimize reconstruction loss, handling of multilingual datasets like LJSpeech or CSS10, exercises on overfitting and regularization, production of customized voices for business cases, analysis of learning curves and real-time tested audio deliverables for rapid skill development.

Module 3Neural TTS Fine-tuning: Transfer Learning and Distillation (FastSpeech, VITS)

Apply transfer learning on pre-trained models like VITS or FastPitch, knowledge distillation techniques to accelerate Neural TTS inference, adaptation to specific voices with limited data via few-shot learning, practical workshops on ethical voice cloning, optimization for edge devices with ONNX, generation of prosodic sample batches, comparative evaluation and documentation of production-ready models.

Module 4Neural TTS Deployment: APIs and Containers (Docker, Kubernetes, streaming)

Integrate Neural TTS into REST APIs with FastAPI and Flask, Docker containerization for scalability, Kubernetes deployment with Prometheus monitoring, implementation of real-time voice streaming via WebSockets, load testing on 1000 simultaneous requests, securing GDPR-compliant voice endpoints, exercises on your red thread project with AWS or GCP cloud deployment, immediate enterprise value.

Module 5Advanced Neural TTS Applications: Evaluation and Ethics (MOS, bias, multimodal)

Evaluate your Neural TTS models with MOS, PESQ, and ASVab metrics, audits for vocal biases and diversity, multimodal integration with vision for talking avatars, workshops on real-world AI assistant and professional audiobook cases, ethical best practices and audio watermarking, finalization of the red thread project with presentation, post-training action plan for production deployment and certified skill enhancement.