What speech-to-text development includes
Aranv provides speech-to-text development for US businesses that record calls, meetings, dictation or field notes. We integrate transcription APIs or open speech recognition models into your software, add speaker labels, custom vocabulary and summaries, and send searchable transcripts to the CRM, case file or job record where your team works.
Speech-to-text, also called automatic speech recognition, converts spoken audio into written text. On its own a transcript is a long block of words. The useful part comes next: speaker labels, timestamps, summaries, extracted fields and filing to the right record.
If you need a system that talks back to callers, see AI voice agent development; this page covers listening and writing down. For analysis across many calls, such as topics, required phrases and talk time, AI call analytics goes further, and AI meeting summaries covers internal meetings.
How recorded speech becomes usable text
From audio file to record
- 01 Capture clean audio Phone systems, meeting tools or a mobile app send audio in a suitable format.
- 02 Transcribe and label speakers A speech model turns audio into text and marks who said each line.
- 03 Correct domain terms Product names, street names or part numbers are fixed with custom vocabulary.
- 04 File the transcript Text, summary and action items attach to the right customer, case or job.
Audio quality decides most of the result, so we test with your real recordings rather than studio samples.
Speech recognition integration across your business
Speech-to-text helps wherever people talk through work that someone later has to type up.
Call transcription and search
Sales and support calls transcribed with speaker labels, searchable by phrase and linked to the contact record in your CRM.
Meeting and interview notes
Recorded meetings, interviews and site visits turned into transcripts with a short summary and a list of agreed actions.
Dictation in field apps
Technicians, inspectors and drivers speak notes into a phone app that fills the report form, even while wearing gloves.
Captions and accessibility
Captions and transcripts for training videos, webinars and recorded announcements, with a review step before anything is published.
Transcription API and engine selection
Speech recognition can come from a dedicated transcription API, the speech service of your cloud provider, or an open model on your own servers. We compare them on your recordings for word accuracy, speaker labels, accents, jargon, delay and cost per audio hour, and build so the engine can be swapped later.
What we do
- Side-by-side tests on your audio
- Batch and real-time streaming modes
- Custom vocabulary and phrase hints
- Speaker diarization and timestamps
- Engine swap without app changes
Consent, sensitive data and review
Recorded speech often includes card numbers, health details and names. We add the consent messages your legal adviser approves, redact sensitive values from transcripts, and set how long audio and text are kept. Where a transcript feeds a legal, medical or financial record, a person reviews it before it is filed.
What we do
- Recording consent messages
- Redaction of card and ID numbers
- Retention schedule for audio and text
- Reviewer step for official records
- Access logs on transcripts
How we approach a project
Transcripts often feed a language model that writes a summary or fills a form. Our LLM integration team builds that step and tests each summary against its transcript, so it does not report things nobody said. Phone audio is usually poorer than meeting audio, so each source is tested separately.
Got recordings and a system they should feed? Share a few minutes of typical audio, with personal details removed, and talk it over with our engineers in a 30-minute conversation booked from the contact page.
How we work
- Tested on your real recordings
- Consent and retention set first
- Transcripts filed in the right record
Our Process
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Audio sample review
We listen to a sample of your calls or recordings and note line quality, accents, jargon and crosstalk.
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Engine bake-off
Two or three speech engines transcribe the same sample, and we score word errors and speaker labels by hand.
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Pipeline and vocabulary
We connect the audio source, add your product and place names as custom vocabulary, and write transcripts to the target system.
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Spot checks after launch
A sample of transcripts is checked each month, and new terms or new audio sources join the test set.
Why Aranv for speech projects
Tested on your phone lines
We judge engines on your own recordings, noisy calls included, so the choice reflects real line quality rather than a vendor’s clean samples.
Not tied to one engine
The transcription provider sits behind a thin adapter, so you can change engines as prices or accuracy shift without rebuilding the app.
Sensitive details removed
Card numbers, IDs and other values you name are redacted from transcripts, and audio retention follows a schedule agreed before launch.
Filed where staff look
Each transcript is matched to the customer, matter or job it belongs to, so nobody searches a separate tool to find what was said.
Planning Speech-to-Text Development?
Book a 30-minute conversation with the team that would build it.
Speech-to-text FAQs
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How accurate is speech to text for business calls?
On clear audio, current speech models are accurate enough for search and summaries, but phone lines, accents, crosstalk and specialist terms all lower accuracy. We measure word error rate on your own recordings before launch, so you know which uses are safe and which need a human check.
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Should we use a transcription API or run our own model?
A cloud transcription API is the quickest start and suits most volumes. Running an open model on your own servers makes sense when audio cannot leave your environment, or when volume is high enough that hosting costs less than per-minute fees. We test both before you commit.
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Can speech recognition tell different speakers apart?
Yes. Speaker diarization labels each segment by speaker and works best when people do not talk over each other. Recording each phone channel separately gives the cleanest result, because agent and caller arrive already split.
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Do we need consent to record and transcribe calls?
Usually, and the rules depend on where each party is located. Several states expect every participant to agree before a call is recorded. We build the consent message and recording controls you choose, and recommend that your legal adviser confirm the wording for the states you serve.
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Can transcripts be saved to our CRM or case management system?
Yes. Transcripts, summaries and extracted fields can attach to a contact, ticket, matter or job through the system’s API. We match each recording to its record using the phone number, meeting invite or job number, and send any recording without a match to a person to file.
Let’s talk about your next step
Contact Aranv to discuss your workflow, current tools, and goals. Meet with our team or send an inquiry.
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