Speech To Text Development
Speech to Text Services That Survive Accents, Noise And Jargon
Recognition looks solved on a quiet recording of a native speaker reading a script. It gets hard on a contact centre line, a warehouse floor or a clinician dictating drug names. We build speech to text that is measured on your own audio and improved against it.
Triple Protection Guarantee
- US-Registered Entity
- Signed IP Assignment
- Senior Engineers Only
Triple Protection Guarantee:
- US-Registered Entity
- Signed IP Assignment
- Senior Engineers Only
Years In Business
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Engineers On Staff
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Avg. Engineer Exp.
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Where STT Goes Wrong
Accent Coverage
Tested Out
Senior Engineers
Vetted Only
Timezone Overlap
Live Hours
Domain Words
Boost List In
Delaware LLC
US Entity
Speaker Labels
Split Apart
Error Analysis
Every Model
Audio Retention Set
In Writing
Latency Path
Streaming
IP Assignment
Signed
Delivery Overlap
Fixed
Hours
Transcript Owner
You
Trusted By Startups
What Our Speech to Text Services Actually Cover
Speech to text services earn their fee on the audio nobody demos. A caller on a bad line talking over an agent. A field engineer in a plant room. A specialist using terms no general model has seen. The work is a vocabulary your model is told about, a pipeline that cleans the audio before it ever reaches a decoder, and an evaluation set of your own recordings that tells you whether a change helped.
Stallyons is registered in Delaware as a US company, and our engineers work a time-zone window agreed before the project starts, with four-plus hours of daily overlap. You sign a US contract, run diligence on a US entity and pay one US invoice. Behind the work sits twelve-plus years of delivery across six continents and around thirty-five engineers, averaging four-plus years of production experience. Teams come to us when transcripts have to be trusted by a business process rather than skimmed by a person.
What A Recognition Build Covers
An evaluation set built from your own recordings before any tuning starts: your speakers, the conditions they record in, transcribed by hand once, so every later change can be judged against the same audio rather than an impression.
A vocabulary the model is told about: your product names, drug names, part numbers, acronyms and place names supplied as phrase hints or a custom language model, so the words that matter are the ones it gets right.
An audio pipeline that runs before the decoder: channel splitting on two-party calls, resampling, noise and echo handling, and voice activity detection, because most recognition failures start in the audio.
Structure in the output, not just words: speaker labels, word-level timestamps, punctuation, and numbers, dates and currency formatted the way your downstream systems expect to read them.
Data handling written down: what is stored, for how long, who can play it back, and where sensitive spans are removed from both the recording and the transcript before anyone sees them.
One accountable vendor: one contract, one invoice and one entity for legal and finance to run diligence on, instead of a spread of contractors across four jurisdictions.
What To Ask A Speech Recognition Software Development Firm
- Ask them to run your worst audio, not their sample file. Every engine sounds capable on a clean recording, and your hardest calls are where the difference actually shows.
- Ask how your own terminology gets in. If there is no route for phrase hints or a custom vocabulary, every product name you launch becomes a transcript defect.
- Ask how they will know whether a change helped. Without a labelled set of your recordings, tuning is opinion, and last month's fix cannot be defended.
- Ask what happens to the recordings. Storage location, retention period, playback rights and redaction of sensitive spans are decisions, and they belong in the contract.
- Ask whether it must be live. Streaming and batch recognition are different builds, and choosing wrongly costs either latency the user feels or money you did not need.
- Ask who reviews the low-confidence output. Some transcripts feed a person and some feed a workflow, and the second kind needs a human check before it is trusted.
How A Speech To Text Project Starts
Every project starts with a free 45-minute scoping session. No slide deck, no sales script. You bring the recordings, the speakers and what the transcript is for; you leave with a build plan and a timeline.
We are selective about new projects and cap how many we run at once, because the scoping is the product. If your audio needs better microphones before it needs a model, we will say so before you buy.
Why Clients Choose Us
Full
Written IP Transfer
USA
Contract Entity
Yours
Audio & Transcript
Named
Delivery Lead
Ready to get usable transcripts out of real audio?
What We Build With STT Audio
The Speech to Text Work We Deliver
Every product is different and the underlying jobs repeat: clean the audio, teach the model your words, decide whether it runs live, and shape the output. These are the recognition builds we deliver most often.
Real-Time Transcription
Streaming audio, partial results
End-to-End
Batch Transcripts
Large archives, queued jobs
Bulk Processed
Speaker Labels
Diarization, turns, speaker counts
Who Spoke
Contact Centre Audio
Telephony lines, crosstalk, noise
Live In Production
Offline STT
On-device models, no upload
No Signal OK
Subtitles & Captions
SRT, VTT, word timestamps
Readable
STT API Integration
Provider routing, quotas, fallback
Linked
Accuracy Evaluation
Labelled test sets, error analysis
Sign-Off
Vocabulary Tuning
Phrase hints, custom language models
Future-Proof
Support & Retraining
Monitoring, drift checks, updates
Kept Running
Not sure which audio you need transcribed? Let us map it.
Common Challenges
Why Do Speech To Text Builds Break?
Six patterns behind almost every transcription feature that has to be rebuilt. All six start with clean test audio.
One Accent Tested
01
The build is validated on the team's own voices. It then meets regional accents, second-language speakers and people who talk over each other, and the transcripts stop being usable for the users who need them most.
Jargon Not Recognised
02
Part numbers, drug names and internal acronyms come back as something that sounds similar. Nobody told the model those words exist, so it guesses the nearest match.
Noise Not Modelled
03
Testing happens on a headset in a quiet room. Production is a speakerphone in a van. The model was never the problem; the audio reaching it was.
Audio Kept Forever
04
Recordings and transcripts pile up with no retention rule and no redaction, so card numbers and health details sit in a bucket somebody will eventually have to explain.
No Way To Measure It
05
There is no labelled set of your own audio, so quality is judged by whoever last listened to a clip. Two changes later nobody can say whether the system improved or drifted.
Only One Speaker Assumed
06
The transcript is one wall of text. Nobody can tell the agent from the caller, quoting a line is guesswork, and the recording cannot be searched by who said it.
Recognise a few of these? Let us do it properly.
Our Speech Services
6 Speech to Text Services We Offer
Six ways to buy recognition from one accountable vendor. Run one, or run several in parallel under a single contract.
Custom STT Product Builds
01
End-to-end delivery of a defined recognition feature: scope, audio pipeline, model choice, evaluation and release, with a named lead who reports into you rather than an account manager.
Audio Pipeline Work
02
Channel splitting, resampling, noise and echo handling and voice activity detection, built and tuned on your own recordings rather than on a generic reference clip.
Custom Language Models
03
Your terminology taught to the model through phrase hints, boosted word lists or a fine-tuned model where the domain justifies the extra work.
Diarization & Timestamps
04
Who spoke, when they spoke and exactly where each word sits in the recording, so transcripts can be searched, quoted, captioned and played back in context.
STT API & Backend Work
05
The services behind the transcript, built by our own API development practice: audio ingestion, job queueing, transcript storage and webhooks.
Accuracy Evaluation Runs
06
A labelled set of your recordings, a repeatable scoring run and error analysis by speaker, accent and condition, so every tuning decision can be defended.
Not sure which piece you need first? Let us scope it together.
Why Choose Us
What Makes Our Speech to Text Services Different
The details that decide whether a transcript can be trusted by a process, not just skimmed.
A US Legal Entity
01
Stallyons is registered in Delaware. Your contract, your invoice and your legal recourse sit with a US company, not an unknown one.
Measured On Your Audio
02
Quality is scored against a labelled set of your own recordings, so improvements are evidence rather than an impression from a demo.
Overlap You Set
03
You choose the hours we share with your working day, and stand-ups, reviews and escalations all happen inside that window.
Audio Handled Safely
04
Storage location, retention, playback rights and redaction of sensitive spans are agreed in writing before the first recording is processed.
Reviewed Code
05
Every merge is reviewed against an agreed definition of done, on your board, where you can read it yourself.
One Contract
06
One contract covers the engagement, so procurement, legal and finance each deal with a single named counterparty.
Ready to see what a proper transcript looks like?
Our Process
From First Call To Live Transcription In Six Steps
A build process that settles audio, vocabulary and evaluation before any transcripts ship.
Discovery
Understand the audio, speakers and use case
Scoping
Agree languages, scope, latency and cost
Design
Audio pipeline, vocabulary and output format
Contracting
NDA, IP assignment, access and onboarding
Deliver
Built, evaluated, reviewed on merge
Tune & Monitor
Analyse errors, then retune the vocabulary
Want to see how this maps to your roadmap?
Technology Stack
What Our Speech to Text Engineers Work With
The recognition engines, audio tooling and pipelines we build transcription on, and what runs them.
Speech Engines
Whisper Models
OpenAI Speech
Google Cloud STT
Amazon ASR
Open Models
Vocabulary & Language
Phrase Hints
Custom Vocabulary
Language IDs
Phonemes
Word Timestamps
Audio Pipeline
WAV, FLAC, Opus
Sample Rates
Noise & Echo Cleanup
Channel Split
Voice Activity Gate
Output & Delivery
SRT & VTT Files
JSON Output
Redacted PII
Confidence Scores
Firebase Delivery
Build & Deliver
Python Services
Node Runtime
Docker Packaging
GitHub Actions / CD
Datadog Monitoring
Who We Build This For
Speech to Text Services For Every Kind Of Product
Eight kinds of product with different audio and one shared need: a transcript the business can rely on.
Contact Centre Ops
Call transcripts, QA scoring
Healthcare & Clinics
Dictation, notes, clinical terms
Legal & Compliance
Hearings, records, retention
EdTech & Lectures
Lecture capture, searchable notes
Media & Broadcasting
Subtitles, archive search, tags
Fintech & Compliance Ops
Call records, audit evidence
Logistics & Field
Hands-free notes, dispatch
Podcasting & Creators
Show notes, chapters, search
Working in another sector? See all industries we serve.
How We Compare
Your Speech to Text Build Options, Compared
An honest look at your four delivery options.
| Capability | Raw API Wiring | In-House Generalist | Freelance Audio Dev | Stallyons Technologies |
|---|---|---|---|---|
| Accent and dialect coverage | ✕ Default model only | Team voices tested | Sample clips | Your speakers, your conditions |
| Your domain vocabulary | ✕ Not supplied | Fixed after complaints | A few hints | Maintained word lists |
| Speaker labels and timestamps | Off by default | Added later | Sometimes included | Diarized, word aligned |
| Real time versus batch | ✕ One mode only | Decided late | ✕ No latency budget | Chosen against a budget |
| How quality is measured | ✕ Vendor claims | Spot listening | By ear | Labelled set, repeatable run |
| Sensitive audio and redaction | ✕ Stored as is | Policy comes later | ✕ Undocumented | Retention and redaction agreed |
| Provider fallback and portability | Single vendor | One integration | ✕ Hardwired | Routed, engine swappable |
See the difference for yourself
Complete Engagement
Everything Included In Your Speech to Text Build
From Scoping to Contracting to Delivery, One Vendor
Here is everything included when you build transcription with us:
One Speech Build Price: No Hidden Fees And No Surprises.
Every recognition engagement includes all eight components above. One contract, one senior team, one predictable cost, and no vendor sprawl.
🔒 No obligation. We'll deliver a detailed proposal within 48 hours.
Plus, Get These Free Bonuses
Free Transcript Review
A written read on your audio quality, vocabulary gaps, output structure and data handling, with the fixes ordered by what costs you most today.
Included Free
Build Plan And Estimate
A phased build plan with scope, milestones, the integrations it needs and a transparent, itemised estimate for the engagement.
Included Free
Free Vendor Checklist
The questions we would ask any speech recognition vendor about audio, vocabulary, evaluation and retention, so you can put them to us too.
Included Free
Risk-Free Partnership
Our Speech To Text Promise
We stand behind every engagement with commitments that protect your investment.
01
Scope Agreed First
Scope, languages, working hours and cost structure are written down and agreed before contracting, so nothing is discovered later.
02
Built to Last
Senior developers, code review, automated tests, security and accessibility audits, and clean, documented code you fully own.
03
IP And Access Protected
NDA and IP assignment are signed before access, permissions are scoped per person, and your accounts stay under your control.
Start your transcription build with confidence, backed by our Triple Protection Guarantee.
Track Record
Engagements That Ship, Scale, and Compound
500+
Projects Delivered
29+
Service Categories
81%
Repeat Client Rate
4.9 ★
Clutch Rating
"Stallyons took our Figma design and built it into a live web application, a cognitive game with level-based match play, messaging, a tutorial, and a directory that ranks users nationally. What impressed me most was their grasp of the code behind that logic, and the quality of the experience. Delivered on time with steady updates."
Jerry L.
Founder
PicCiti LLC
"We brought Stallyons in to absorb an overflow of work, and they delivered ten iOS and Android apps, from reporting to geo-location for logistics, plus several backend systems, owning design, development, and app-store submission. Everything stood out: code quality, speed, and reliability. Perfect code, on time, adopted company-wide."
William B.
Director
Amplo Solutions
FAQ
Frequently Asked Speech To Text Questions
Speech to text services turn spoken audio into usable text inside your own product. In practice that means an audio pipeline that cleans and splits the recording, a vocabulary the model is told about so your own terms come through, speaker labels and word-level timestamps in the output, a decision about live or batch processing, and an evaluation set of your recordings that shows whether a change helped.
Speech to text is one component: audio goes in, text comes out. A conversational voice agent is a whole system that also works out intent, decides what to do next, holds a turn-taking conversation and speaks back, with recognition as its first step. If you need transcripts, captions, dictation or voice input inside your product, this page is the right one. If you need something that answers callers and completes tasks, see conversational voice systems.
Build cost follows how difficult your audio is, how much vocabulary work the domain needs, whether output must be structured for a downstream system, and whether recognition runs live. Running cost is billed by the provider per hour of audio, so batching and filtering silence move it. We scope first, then price, and itemise each phase so you can cut before you commit.
By building a labelled set from your own recordings and scoring against it every time something changes. Errors are then grouped by speaker, accent, channel and background condition, because a single overall figure hides which cohort is failing. Vendor benchmark numbers do not predict your result, since they were measured on audio that is nothing like yours.
You do, from the first day. The recordings, the transcripts, the vocabulary lists, the evaluation set and the repositories are yours, and provider accounts are registered in your name. NDA and IP assignment are signed before anyone gets access, and retention rules are agreed in writing first.
That depends on the engine, and it is a scoping question rather than a marketing one. Major languages are broadly covered; regional accents, second-language speakers and code-switching between two languages in one sentence are where the real differences appear. We test your candidate engines on your own recordings before recommending one.
It depends on whether someone is acting on the words as they are spoken. Streaming returns partial results while the speaker is still talking, which suits live captions, dictation and agent assistance. Batch processes the finished recording, handles noisy audio better because it can see the whole file, and costs less to run.
Often, and they are separate engineering problems rather than two halves of one job. Recognition is about accents, noise, vocabulary and timestamps; synthesis is about voice, pronunciation and prosody. We scope them together when a product needs both. The synthesis side is covered on our text to speech page.
Still have questions? Let's talk.
Schedule an appointment with us today!
Ready To Build Speech To Text That Works?
Get a free consultation. We will listen to your real audio, name what will go wrong, and send a written proposal.
