Requesting NICE CXone Compliance Recording Transcriptions via API with Python

What You Will Build

• The code submits compliance recording identifiers to the NICE CXone Voice Transcription API, polls for asynchronous job completion, and structures the output for legal review.
• This tutorial uses the NICE CXone /api/v2/voice/transcriptions endpoint and standard HTTP REST interactions.
• All examples are implemented in Python 3.9+ using the requests library.

Prerequisites

• OAuth 2.0 Client Credentials grant with scopes: recordings:read voice:transcribe
• NICE CXone API v2 (REST)
• Python 3.9 or higher
• External dependencies: requests, pydantic, tenacity, jsonlines

Authentication Setup

The NICE CXone platform requires OAuth 2.0 Client Credentials flow. You must obtain an access token before issuing transcription requests. The token endpoint returns a bearer token valid for 3600 seconds. You must cache the token and refresh it before expiration to avoid 401 Unauthorized errors during long-running polling cycles.

import requests
import time
from typing import Optional

class CxoneAuthManager:
    def __init__(self, org_domain: str, client_id: str, client_secret: str):
        self.org_domain = org_domain
        self.client_id = client_id
        self.client_secret = client_secret
        self.token_url = f"https://{org_domain}/oauth2/token"
        self.access_token: Optional[str] = None
        self.token_expiry: float = 0.0

    def get_token(self) -> str:
        if self.access_token and time.time() < self.token_expiry - 60:
            return self.access_token

        payload = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret,
            "scope": "recordings:read voice:transcribe"
        }

        response = requests.post(self.token_url, data=payload, timeout=15)
        response.raise_for_status()
        data = response.json()

        self.access_token = data["access_token"]
        self.token_expiry = time.time() + data["expires_in"]
        return self.access_token

OAuth Scope Requirement: recordings:read voice:transcribe
The recordings:read scope allows the client to validate recording metadata and storage quotas. The voice:transcribe scope grants permission to submit transcription jobs and retrieve results.

Implementation

Step 1: Payload Construction and Schema Validation

The transcription request payload must include recording identifiers, language locale directives, and redaction policy parameters. You must validate the payload against media format constraints and storage quota limits before submission. NICE CXone rejects transcription jobs for recordings exceeding configured storage thresholds or unsupported audio codecs.

import pydantic
from typing import List
import requests

class TranscriptionRequest(pydantic.BaseModel):
    recording_ids: List[str]
    language: str = "en-US"
    redaction_policy: str = "pii"
    punctuation: bool = True
    diarization: bool = True
    webhook_url: str

class ComplianceTranscriptionRequester:
    def __init__(self, auth: CxoneAuthManager, base_url: str, max_storage_mb: int = 500):
        self.auth = auth
        self.base_url = base_url.rstrip("/")
        self.max_storage_mb = max_storage_mb
        self.session = requests.Session()
        self.session.headers.update({"Content-Type": "application/json"})

    def validate_recordings(self, recording_ids: List[str]) -> None:
        """Validates media format and storage quota before transcription submission."""
        token = self.auth.get_token()
        self.session.headers["Authorization"] = f"Bearer {token}"

        # Paginate recording metadata fetch
        offset = 0
        limit = 100
        total_storage = 0.0

        while offset < len(recording_ids):
            batch = recording_ids[offset:offset + limit]
            ids_param = "&ids=".join(batch)
            url = f"{self.base_url}/api/v2/recordings?ids={ids_param}"
            
            response = self.session.get(url, timeout=15)
            response.raise_for_status()
            recordings = response.json().get("entities", [])

            for rec in recordings:
                if rec.get("format") not in ("wav", "mp3"):
                    raise ValueError(f"Unsupported media format: {rec.get('format')} for {rec['id']}")
                total_storage += rec.get("size", 0) / (1024 * 1024)

            offset += limit

        if total_storage > self.max_storage_mb:
            raise ValueError(f"Storage quota exceeded: {total_storage:.2f} MB exceeds limit of {self.max_storage_mb} MB")

Expected Response Structure:

{
  "entities": [
    {
      "id": "rec_8a7f3b2c1d4e",
      "format": "wav",
      "size": 4194304,
      "mediaType": "audio/wav"
    }
  ],
  "pageSize": 1,
  "pageNumber": 1,
  "total": 1
}

Step 2: Asynchronous Job Submission and Polling with Retry Logic

Transcription jobs run asynchronously on NICE speech infrastructure. You must poll the job status endpoint until completion. Transient speech service unavailability returns HTTP 503 or 429. You must implement exponential backoff retry logic to prevent cascade failures.

from tenacity import retry, stop_after_attempt, wait_exponential, retry_if_exception_type
import requests.exceptions

    @retry(
        stop=stop_after_attempt(5),
        wait=wait_exponential(multiplier=2, min=4, max=60),
        retry=retry_if_exception_type((requests.exceptions.HTTPError, requests.exceptions.ConnectionError)),
        reraise=True
    )
    def submit_transcription(self, payload: TranscriptionRequest) -> str:
        """Submits transcription job and returns job identifier."""
        token = self.auth.get_token()
        self.session.headers["Authorization"] = f"Bearer {token}"

        request_body = payload.dict()
        url = f"{self.base_url}/api/v2/voice/transcriptions"

        response = self.session.post(url, json=request_body, timeout=30)
        
        if response.status_code == 429:
            retry_after = int(response.headers.get("Retry-After", 5))
            raise requests.exceptions.HTTPError(f"Rate limited. Retry after {retry_after}s")
        
        response.raise_for_status()
        return response.json()["id"]

    def poll_transcription_status(self, job_id: str) -> dict:
        """Polls job status with progress tracking until completion or failure."""
        token = self.auth.get_token()
        self.session.headers["Authorization"] = f"Bearer {token}"
        url = f"{self.base_url}/api/v2/voice/transcriptions/{job_id}"

        while True:
            response = self.session.get(url, timeout=15)
            response.raise_for_status()
            job_data = response.json()

            status = job_data.get("status")
            progress = job_data.get("progress", 0)
            print(f"Job {job_id}: status={status}, progress={progress}%")

            if status in ("completed", "failed"):
                return job_data
            
            if status == "in_progress":
                import time
                time.sleep(10)
            else:
                raise RuntimeError(f"Unexpected job status: {status}")

Error Handling: The tenacity decorator automatically retries on 429 Too Many Requests and 503 Service Unavailable. The polling loop breaks only on completed or failed states. Connection timeouts trigger immediate retry cycles.

Step 3: Text Processing Pipeline and Webhook Synchronization

Raw ASR outputs require punctuation restoration and speaker diarization structuring. You must parse the results array, apply text normalization, and synchronize completion status with external legal review platforms via webhook callbacks.

import json
import time
import jsonlines
from typing import Dict, Any

    def process_transcription_results(self, job_data: dict) -> Dict[str, Any]:
        """Structures raw ASR output with punctuation restoration and diarization."""
        results = job_data.get("results", [])
        processed_segments = []

        for segment in results:
            text = segment.get("text", "")
            speaker_label = segment.get("speakerLabels", ["unknown"])[0]
            confidence = segment.get("confidence", 0.0)

            # Punctuation restoration pipeline
            if self._needs_punctuation(text):
                text = self._restore_punctuation(text)

            processed_segments.append({
                "speaker": speaker_label,
                "text": text,
                "confidence": confidence,
                "start_ms": segment.get("startOffsetMs"),
                "end_ms": segment.get("endOffsetMs")
            })

        return {
            "transcription_id": job_data["id"],
            "status": job_data["status"],
            "accuracy_score": job_data.get("accuracyScore", 0.0),
            "processed_segments": processed_segments,
            "completed_time": job_data.get("completedTime")
        }

    def _needs_punctuation(self, text: str) -> bool:
        return not any(text.endswith(p) for p in (".", "!", "?", ";", ":"))

    def _restore_punctuation(self, text: str) -> str:
        """Basic punctuation restoration for compliance text normalization."""
        text = text.strip()
        if text.lower().startswith(("who", "what", "when", "where", "why", "how")):
            return f"{text}?"
        return f"{text}."

    def write_audit_log(self, job_id: str, result: Dict[str, Any], duration_ms: float) -> None:
        """Generates regulatory compliance audit logs."""
        audit_entry = {
            "timestamp": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
            "transcription_job_id": job_id,
            "status": result["status"],
            "accuracy_score": result["accuracy_score"],
            "processing_duration_ms": duration_ms,
            "segment_count": len(result["processed_segments"]),
            "compliance_flags": {
                "pii_redacted": True,
                "diarization_applied": True,
                "punctuation_restored": True
            }
        }

        with jsonlines.open("transcription_audit.log", mode="a") as writer:
            writer.write(audit_entry)

    def execute_full_pipeline(self, request: TranscriptionRequest) -> Dict[str, Any]:
        """Orchestrates submission, polling, processing, and audit logging."""
        self.validate_recordings(request.recording_ids)
        start_time = time.perf_counter()

        job_id = self.submit_transcription(request)
        job_data = self.poll_transcription_status(job_id)
        
        duration_ms = (time.perf_counter() - start_time) * 1000
        processed = self.process_transcription_results(job_data)
        self.write_audit_log(job_id, processed, duration_ms)

        # Webhook synchronization is handled server-side by CXone using request.webhook_url
        # Client-side verification can be added here if required
        return processed

Expected Response Structure (Polling):

{
  "id": "txn_9f8e7d6c5b4a",
  "status": "completed",
  "progress": 100,
  "accuracyScore": 0.94,
  "createdTime": "2024-01-15T10:00:00Z",
  "completedTime": "2024-01-15T10:02:30Z",
  "results": [
    {
      "text": "i need to verify my account balance",
      "speakerLabels": ["agent"],
      "confidence": 0.98,
      "startOffsetMs": 1200,
      "endOffsetMs": 3400
    },
    {
      "text": "please provide your last four digits",
      "speakerLabels": ["customer"],
      "confidence": 0.91,
      "startOffsetMs": 3500,
      "endOffsetMs": 5100
    }
  ]
}

Complete Working Example

The following script combines authentication, validation, submission, polling, processing, and audit logging into a single executable module. Replace placeholder credentials with your NICE CXone organization values.

import requests
import time
import pydantic
import jsonlines
from typing import List, Dict, Any, Optional
from tenacity import retry, stop_after_attempt, wait_exponential, retry_if_exception_type
import requests.exceptions

class CxoneAuthManager:
    def __init__(self, org_domain: str, client_id: str, client_secret: str):
        self.org_domain = org_domain
        self.client_id = client_id
        self.client_secret = client_secret
        self.token_url = f"https://{org_domain}/oauth2/token"
        self.access_token: Optional[str] = None
        self.token_expiry: float = 0.0

    def get_token(self) -> str:
        if self.access_token and time.time() < self.token_expiry - 60:
            return self.access_token

        payload = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret,
            "scope": "recordings:read voice:transcribe"
        }

        response = requests.post(self.token_url, data=payload, timeout=15)
        response.raise_for_status()
        data = response.json()

        self.access_token = data["access_token"]
        self.token_expiry = time.time() + data["expires_in"]
        return self.access_token

class TranscriptionRequest(pydantic.BaseModel):
    recording_ids: List[str]
    language: str = "en-US"
    redaction_policy: str = "pii"
    punctuation: bool = True
    diarization: bool = True
    webhook_url: str

class ComplianceTranscriptionRequester:
    def __init__(self, auth: CxoneAuthManager, base_url: str, max_storage_mb: int = 500):
        self.auth = auth
        self.base_url = base_url.rstrip("/")
        self.max_storage_mb = max_storage_mb
        self.session = requests.Session()
        self.session.headers.update({"Content-Type": "application/json"})

    def validate_recordings(self, recording_ids: List[str]) -> None:
        token = self.auth.get_token()
        self.session.headers["Authorization"] = f"Bearer {token}"
        offset = 0
        limit = 100
        total_storage = 0.0

        while offset < len(recording_ids):
            batch = recording_ids[offset:offset + limit]
            ids_param = "&ids=".join(batch)
            url = f"{self.base_url}/api/v2/recordings?ids={ids_param}"
            
            response = self.session.get(url, timeout=15)
            response.raise_for_status()
            recordings = response.json().get("entities", [])

            for rec in recordings:
                if rec.get("format") not in ("wav", "mp3"):
                    raise ValueError(f"Unsupported media format: {rec.get('format')} for {rec['id']}")
                total_storage += rec.get("size", 0) / (1024 * 1024)

            offset += limit

        if total_storage > self.max_storage_mb:
            raise ValueError(f"Storage quota exceeded: {total_storage:.2f} MB exceeds limit of {self.max_storage_mb} MB")

    @retry(
        stop=stop_after_attempt(5),
        wait=wait_exponential(multiplier=2, min=4, max=60),
        retry=retry_if_exception_type((requests.exceptions.HTTPError, requests.exceptions.ConnectionError)),
        reraise=True
    )
    def submit_transcription(self, payload: TranscriptionRequest) -> str:
        token = self.auth.get_token()
        self.session.headers["Authorization"] = f"Bearer {token}"
        request_body = payload.dict()
        url = f"{self.base_url}/api/v2/voice/transcriptions"

        response = self.session.post(url, json=request_body, timeout=30)
        
        if response.status_code == 429:
            retry_after = int(response.headers.get("Retry-After", 5))
            raise requests.exceptions.HTTPError(f"Rate limited. Retry after {retry_after}s")
        
        response.raise_for_status()
        return response.json()["id"]

    def poll_transcription_status(self, job_id: str) -> dict:
        token = self.auth.get_token()
        self.session.headers["Authorization"] = f"Bearer {token}"
        url = f"{self.base_url}/api/v2/voice/transcriptions/{job_id}"

        while True:
            response = self.session.get(url, timeout=15)
            response.raise_for_status()
            job_data = response.json()

            status = job_data.get("status")
            progress = job_data.get("progress", 0)
            print(f"Job {job_id}: status={status}, progress={progress}%")

            if status in ("completed", "failed"):
                return job_data
            
            if status == "in_progress":
                time.sleep(10)
            else:
                raise RuntimeError(f"Unexpected job status: {status}")

    def process_transcription_results(self, job_data: dict) -> Dict[str, Any]:
        results = job_data.get("results", [])
        processed_segments = []

        for segment in results:
            text = segment.get("text", "")
            speaker_label = segment.get("speakerLabels", ["unknown"])[0]
            confidence = segment.get("confidence", 0.0)

            if not any(text.endswith(p) for p in (".", "!", "?", ";", ":")):
                if text.strip().lower().startswith(("who", "what", "when", "where", "why", "how")):
                    text = f"{text}?"
                else:
                    text = f"{text}."

            processed_segments.append({
                "speaker": speaker_label,
                "text": text,
                "confidence": confidence,
                "start_ms": segment.get("startOffsetMs"),
                "end_ms": segment.get("endOffsetMs")
            })

        return {
            "transcription_id": job_data["id"],
            "status": job_data["status"],
            "accuracy_score": job_data.get("accuracyScore", 0.0),
            "processed_segments": processed_segments,
            "completed_time": job_data.get("completedTime")
        }

    def write_audit_log(self, job_id: str, result: Dict[str, Any], duration_ms: float) -> None:
        audit_entry = {
            "timestamp": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
            "transcription_job_id": job_id,
            "status": result["status"],
            "accuracy_score": result["accuracy_score"],
            "processing_duration_ms": duration_ms,
            "segment_count": len(result["processed_segments"]),
            "compliance_flags": {
                "pii_redacted": True,
                "diarization_applied": True,
                "punctuation_restored": True
            }
        }

        with jsonlines.open("transcription_audit.log", mode="a") as writer:
            writer.write(audit_entry)

    def execute_full_pipeline(self, request: TranscriptionRequest) -> Dict[str, Any]:
        self.validate_recordings(request.recording_ids)
        start_time = time.perf_counter()

        job_id = self.submit_transcription(request)
        job_data = self.poll_transcription_status(job_id)
        
        duration_ms = (time.perf_counter() - start_time) * 1000
        processed = self.process_transcription_results(job_data)
        self.write_audit_log(job_id, processed, duration_ms)

        return processed

if __name__ == "__main__":
    auth = CxoneAuthManager(
        org_domain="your-org.cxone.com",
        client_id="your_client_id",
        client_secret="your_client_secret"
    )

    requester = ComplianceTranscriptionRequester(
        auth=auth,
        base_url="https://your-org.cxone.com",
        max_storage_mb=500
    )

    compliance_request = TranscriptionRequest(
        recording_ids=["rec_8a7f3b2c1d4e", "rec_1b2c3d4e5f6a"],
        language="en-US",
        redaction_policy="pii",
        punctuation=True,
        diarization=True,
        webhook_url="https://legal-review.internal/api/v1/transcription-callback"
    )

    result = requester.execute_full_pipeline(compliance_request)
    print(json.dumps(result, indent=2))

Common Errors & Debugging

Error: HTTP 401 Unauthorized

• Cause: Expired OAuth token or missing recordings:read voice:transcribe scopes.
• Fix: Verify the CxoneAuthManager refreshes the token before expiration. Ensure the client credentials possess both required scopes in the CXone Admin Console.
• Code Fix: The get_token method automatically refreshes when time.time() >= token_expiry - 60.

Error: HTTP 403 Forbidden

• Cause: Client lacks permission to access voice transcription services or recordings belong to a restricted partition.
• Fix: Assign the Voice: Transcribe and Recordings: Read roles to the OAuth client user in CXone administration. Verify recording IDs belong to the authenticated tenant.

Error: HTTP 429 Too Many Requests

• Cause: Exceeded CXone API rate limits or speech service concurrency thresholds.
• Fix: The tenacity retry decorator handles automatic backoff. Increase min=4 and max=60 parameters if your environment processes high volumes. Implement request queuing in your application layer.

Error: HTTP 400 Bad Request

• Cause: Invalid payload schema, unsupported media format, or storage quota violation.
• Fix: The validate_recordings method checks format (wav, mp3) and cumulative size before submission. Adjust max_storage_mb or split large recording batches into smaller chunks.

Error: HTTP 503 Service Unavailable

• Cause: Transient NICE speech infrastructure unavailability or maintenance window.
• Fix: The retry logic captures ConnectionError and HTTPError for 503 responses. Wait periods double exponentially. If failures persist beyond 15 minutes, check CXone Service Status dashboard.

Official References

• NICE CXone Voice Transcriptions API
• NICE CXone Recordings API
• NICE CXone OAuth 2.0 Authentication
• Pydantic Validation Documentation
• Tenacity Retry Library Documentation