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Master DeepSpeech: Implementing Open Source Speech Recognition

Ref: NXM400
8 people max.
From $2,625 HT / per person
On-site on request · +$540 with certification exam
2 days
Remote

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Microsoft
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Ubisoft
Microsoft
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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)
A child walking to school with a backpack
Our social commitment

A school kit donated to a child for every training

To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.

  • Backpack, notebooks and essential supplies
  • Distributed through our partner charities
  • Included, at no extra cost to you

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 mastery of DeepSpeech for open source speech recognition, 65% of implementations show error rates above 25%, leading to deployment delays of 8 to 12 weeks per project.

  • This costs an average of 35 000 € in wasted development hours and emergency fixes, multiplying the risks of sensitive data leaks.

  • For developers and data scientists, this is a direct threat to their careers: 40% of AI teams stagnate or are reassigned in the face of higher-performing competitors.

  • Each month without these skills exposes the company to a 15% loss in productivity on voice applications, compromising its market position.

Allan BUSI
Allan BUSI

Learni trainer · AI expert

73%productivity gap
×3cost of inaction

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.

Step 1

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.
Step 2

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.
Step 3

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.
Step 4

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.

FAQ

Frequently asked questions

How much does the Master DeepSpeech: Implementing Open Source Speech Recognition training cost?+
The price is $2,625 (USD) per participant. 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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