Rigorous trainer selection
Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.
- Triple validation: technical, pedagogical, sectoral.
- Minimum rating 4.8/5 over the last 12 sessions.
Learning objectives
- Understand the fundamental concepts of automatic speech recognition (ASR)
- Install, configure, and use DeepSpeech in professional projects
- Train a DeepSpeech model on custom datasets
- Adapt and optimize DeepSpeech for different use cases
- Integrate DeepSpeech into a business application (desktop, mobile, or web)
The Learni story
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
Don't let this gap widen
Why this program matters
Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.
Organizations that don't train their talents on key topics see their competitiveness drop.
Every quarter without training is a gap widening with competitors who invest.
The cost of inaction quickly exceeds that of well-targeted training.
Program
Module 1Introduction to Speech Recognition and DeepSpeech
Overview of speech recognition systems (ASR) and modern speech-to-text architectures. Presentation of the DeepSpeech project: history, open source philosophy, advantages, limitations. Installation of DeepSpeech on Linux/Windows, exploration of documentation and community resources. Quick hands-on with DeepSpeech: audio-to-text conversion and result visualization. Introduction to specific vocabulary (acoustic models, language modeling, scores).
Module 2Customization, Training, and Adaptation of DeepSpeech
Presentation of public datasets (Common Voice, LibriSpeech). Collection, preparation, and cleaning of custom audio corpora. Labeling and formatting for DeepSpeech (scripts, ancillary tools). Training a basic DeepSpeech model on a sub-dataset (introduction to GPU). Hyperparameter tuning, initial benchmarks, and performance analysis. Introduction to language model (LM) optimization with KenLM. Deployment on local server or cloud.
Module 3Advanced Integration and Production Optimization
Optimization techniques for production (accuracy and speed). Conversion and adaptation for different audio formats (telephony, meetings, mobile supports). Integration of DeepSpeech into a Python application (REST API, microservices, practical examples). Demonstration of web or business application integration. Security, GDPR, and privacy considerations. Result evaluation, recognition monitoring, and system maintenance. Tips and resources for technology watch.
Evaluation method
- Hands-on exercises after each module
- Multiple-choice quiz at the end of the course
- Presentation of a case study or final project
Learning method
- Interactive courses via videoconference
- Coding workshops
- Provision of notebooks and written materials
- Real-world case studies from industry
Methods, materials and delivery
The Master DeepSpeech: Implementing Open Source Speech Recognition program is delivered onsite or remote (blended-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.
The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.
Equipment required
For the smooth delivery of the Master DeepSpeech: Implementing Open Source Speech Recognition program, the following equipment is required:
- Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
- Training environments installed on workstations or accessible online
- Course materials, hands-on exercises and complementary resources
- Post-training access to materials and educational resources
For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.
* contact us for remote delivery feasibility** ratio varies depending on the program
Skills assessment methods
Assessment of skills acquired during the Master DeepSpeech: Implementing Open Source Speech Recognition program is performed through:
- During training: case studies, hands-on labs and professional scenarios
- End of training: self-assessment questionnaire and skills evaluation by the trainer
- After training: completion certificate detailing acquired skills
Program accessibility
Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.
Enrollment terms and lead times
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
Our method
Training quality, guaranteed at every step
Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.
You meet the trainer beforehand
30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.
- Live briefing on goals and team context.
- Veto right — we swap the trainer for free if needed.
Content tailored to your context
No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.
- Hands-on cases drawn from your stack and projects.
- Program co-written then validated by your team.
Continuous quality follow-up
Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.
- NPS, knowledge quizzes and skills self-assessment.
- Satisfaction guarantee: fully satisfied or free rework.
A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.
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FAQ
Frequently asked questions
How much does the Master DeepSpeech: Implementing Open Source Speech Recognition training cost?+
The individual price is $2,310 (USD). A detailed quote is sent within one business day.
How long is the Master DeepSpeech: Implementing Open Source Speech Recognition training?+
The training lasts 2 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Mastery of Python basics, knowledge of Linux recommended, basic knowledge of Deep Learning recommended
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
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