Find the part number someone said in a noisy meeting
Superlinked gives your agent one API to turn call, meeting and hearing recordings into transcripts it can search and quote.
Um, findings, I've got my nice little picture there. This is uh the chip called the TA double one eight three five which is what's used in pretty much every remote control 'cause it sends out standard signals, based on your input and um it's pretty much used for all all TV 'Kay. remotes at the moment. Um and then we we're loo looking into battery options.
I've got my nice little picture there. This is the chip called the TA11835, which is what's used in pretty much every remote control because it sends out standard signals based on your input. And it's pretty much used for all TV remotes at the moment. And then we're looking into battery options.
Search the transcript TA11835 1 match
- Key terms found
- 5 of 5
- Word error rate
- 9.5%
A search finds 56 of the 61 spoken names, prices and part numbers
Clinician
Something called either nitrofurantoin or trimethoprine. And it's normally a three-day course. So one tablet twice a day for three days.
4.3% word error rate against 23 human-transcribed words
| Human transcript | Whisper |
|---|---|
| Nitrofurantoin | nitrofurantoin |
| Trimethoprim | trimethoprine Missed |
| three day course | three-day course |
| one tablet, twice a day | one tablet twice a day |
| three days | three days |
Shay Dvoretzky, counsel for the taxpayer
There is a recent report from the IRS Taxpayer Advocate showing that between 2004 and 2018, only a little over 1% of levy notices actually resulted in a CDP hearing being sought.
20.0% word error rate against 40 human-transcribed words
| Human transcript | Whisper |
|---|---|
| IRS Taxpayer Advocate | IRS Taxpayer Advocate |
| 2004 | 2004 |
| 2018 | 2018 |
| 1 percent | 1% |
| levy notices | levy notices |
| CDP hearing | CDP hearing |
Project manager (speaker B), with room backchannel
So according to the group, we're going to be selling this remote control for €25 and we're aiming to make €50 million. So we're going to be selling this on an international scale and we don't want it to cost any more than €1250, so 50% of the selling price.
3.7% word error rate against 54 human-transcribed words
| Human transcript | Whisper |
|---|---|
| twenty five Euro | €25 |
| fifty million Euro | €50 million |
| international scale | international scale |
| twelve fifty Euros | €1250 Missed |
| fifty percent | 50% |
“€1250” is a hundred times the spoken €12.50, which the speaker calls fifty percent of the €25 price.
3 of the 12 recorded clips play here, with two more in the hero and the playground. Across all 12, Whisper's pooled word error rate is 8.1% over 594 human-transcribed words, and 5 key terms came back wrong, 2 of them shown above.
One call turns a recording into text your agent can search
from pathlib import Pathfrom sie_sdk import SIEClientclient = SIEClient( api_key="API keysk-sie-…", base_url="https://api.superlinked.com",)audio = {"data": Path(fileMP3scotus-nrc-atomic-energy-act.mp3browse).read_bytes(), "format": "mp3"}result = client.extract( "modelopenai/whisper-large-v3-turbo", {"audio": audio}, instruction="Transcribe the audio verbatim.",)print(result["data"])audio_bytes=$(base64 < 'scotus-nrc-atomic-energy-act.mp3' | tr -d '\n')
curl https://api.superlinked.com/v1/extract/openai%2Fwhisper-large-v3-turbo \
-H "Authorization: Bearer sk-sie-…" \
-H "Content-Type: application/json" \
-d "{\"items\":[{\"audio\":{\"data\":\"$audio_bytes\",\"format\":\"mp3\"}}],\"params\":{\"instruction\":\"Transcribe the audio verbatim.\"}}"Build the "Speech to text" capability into my app using the Superlinked Inference Engine (SIE).
Context
- SIE is an OpenAI-style inference API. Python SDK: `from sie_sdk import SIEClient`; TypeScript: `@superlinked/sie-sdk`.
- Base URL: https://api.superlinked.com (or my regional endpoint). Auth: Bearer key from env `SIE_API_KEY` (never hard-code it).
- Model: openai/whisper-large-v3-turbo (SIE primitive: /extract). Keep the model id configurable.
Task
- Input: an uploaded audio recording.
- Behaviour: return a verbatim transcript of the uploaded audio
- Call the selected SIE primitive once per request and map the response into your domain type.
Deliverables
- A typed client wrapper, an application-level function for this task, error handling for timeouts/empty input, and unit tests with a stubbed client.
- Wire it into my existing stack (ask me which framework if unclear) and add a short usage example.- text
- First, I would point the Court to the licensing provisions in the Atomic Energy Act, which are 42 U.S.C., 2073A, which deals with special nuclear material, 2093, which deals with source material, and 2111, which deals with byproduct material.
- duration_ms
- 18111
- language
- null
Speech to text quality and latency
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Easy & scalable deployment in your own cloud.
- Terraform to your cloud in minutes
- Apache-2.0, same engine as Cloud
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Deploy SIE to our AWS account with the superlinked/sie/aws Terraform module. Docs: superlinked.com/docs/deploymentDeploy SIE to our GCP project with the superlinked/sie/google Terraform module. Docs: superlinked.com/docs/deploymentDeploy SIE to our Azure AKS cluster via helm install. Requirements: superlinked.com/docs/deployment Run locally
Run the same models on your own machine.
- Runs on NVIDIA GPU or Apple Silicon
- One command, no Docker or cluster
- All 100+ Cloud models, fully offline
- Same SDK and IDs, no code changes
pip install "sie-server[local]" && sie-server servepip install "sie-server[local]" && sie-server serve --device cuda