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Speech Revolutions — Python SDK

Official Python client for the Speech Revolutions speech-to-text API.

Install

pip install speechrevolutions

For console progress bars, install the optional tqdm extra:

pip install "speechrevolutions[progress]"

Quick start

from speechrevolutions import SpeechRevolutions

client = SpeechRevolutions()  # reads SPEECHREVOLUTIONS_API_KEY
result = client.transcribe("meeting.mp3", speaker_labels=True)
print(result.text)

for u in result.utterances:
    print(f"Speaker {u.speaker}: {u.text}")

Async

from speechrevolutions import AsyncSpeechRevolutions

async with AsyncSpeechRevolutions() as client:
    result = await client.transcribe("meeting.mp3", speaker_labels=True)
    print(result.text)

From a URL (Deepgram-style)

result = client.transcribe_url("https://example.com/audio.mp3")
# or
result = client.transcribe("https://example.com/audio.mp3")

Options as kwargs or config object

# kwargs (ElevenLabs / Deepgram style). `diarize` is an alias for `speaker_labels`.
result = client.transcribe("a.mp3", diarize=True, output_type="json")

# config object (AssemblyAI style)
from speechrevolutions import TranscribeOptions
result = client.transcribe("a.mp3", options=TranscribeOptions(speaker_labels=True))

Defaults: output_type="json", word_timestamps, speaker_labels, nltk all True, tier="standard", custom_vocabulary=None.

Live progress

Unlike AssemblyAI/Deepgram (which give no percentage for pre-recorded audio), you get real-time progress — for both the file upload and the transcription — as a console bar, a callback, or both.

# 1. Console bars (uses tqdm if installed: pip install "speechrevolutions[progress]")
#    Shows an "Uploading" byte bar, then a "Transcribing" bar.
result = client.transcribe("meeting.mp3", progress=True)

# 2. Programmatic — read event.percent (0–100) to drive your own UI / API
def on_progress(event):        # transcription
    print(event.percent, event.step)      # e.g. 50.0 "chunk:0"

def on_upload(event):          # upload (event.step == "upload")
    print("upload", event.percent)

result = client.transcribe(
    "meeting.mp3",
    on_progress=on_progress,
    on_upload_progress=on_upload,
)

progress=True and the callbacks compose — the bars render and your callbacks still fire for every event.

Result shape

Default output_type is json. The SDK parses it into a transcript-first object:

Field Like
result.text AssemblyAI / ElevenLabs
result.transcript Deepgram alias
result.words word + start/end/speaker
result.utterances AssemblyAI speaker turns
result.to_deepgram() Deepgram-shaped dict
result.to_dict() normalized JSON
result.content / result.save() raw bytes / file
dg = result.to_deepgram()
print(dg["results"]["channels"][0]["alternatives"][0]["transcript"])

Webhooks & retrieving results later

submit() uploads and enqueues a job and returns its id without waiting — ideal for batch/background work. Collect the result later via a webhook (callback_url, a signed POST — verify X-SR-Signature: sha256=… against the raw bytes) or by polling:

job_id = client.submit("meeting.mp3")       # returns immediately, no waiting
# ...or notify a webhook instead of polling:
client.transcribe("meeting.mp3", callback_url="https://you.example.com/hook")

status = client.get_job_status(job_id)      # .status: processing|completed|failed
if status.is_completed:
    result = client.get_transcript(job_id)  # downloads + parses
page = client.list_jobs(limit=50)           # {"jobs": [...], "next_before": ...}

See examples/ for a full submit/poll/webhook walkthrough.

Robustness

SpeechRevolutions(max_retries=3, retry_backoff=0.5, proxies={"https": "..."}). Transient 429/5xx/network errors are retried (honoring Retry-After). Errors are typed (RateLimitError, AuthenticationError, …) and carry .status_code and .request_id for correlating with support.

Auth

export SPEECHREVOLUTIONS_API_KEY=stt_...

Or SpeechRevolutions(api_key="stt_...").

Other languages

Speech Revolutions also publishes SDKs for JavaScript/TypeScript, Go, and C#/.NET — see docs.speechrevolutions.com for a cross-language feature comparison.

License

MIT

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