# Interview Transcripts — String Normalisation + Two-Measure Correlation

> Interview Transcripts — String Normalisation + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).

Normalises transcript_words strings and computes correlation between transcript_words and audio_minutes across up to 200 interview transcript rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-news-12-033?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/interview-transcripts-string-normalisation-two-measure-correlation-5b38c037
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_xjNCG3NPpCjd62-jGhSOI

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability interview-transcripts-string-normalisation-two-measure-correlation-5b38c037 -d '<json body>'
```

Example prompt: Can you normalize the transcript word counts and compute the correlation between transcript_words and audio_minutes for my interview dataset? I have 4 rows: row-1 on 2026-10-01 in group-a with 10 words and 1 minute, row-2 on 2026-10-02 in group-b with 20 words and 2 minutes, row-3 on 2026-10-03 in group-a with 15 words and 3 minutes, and row-4 on 2026-10-04 in group-b with 30 words and 4 minutes.

## When to prefer this

Choose this endpoint when you have tabular interview transcript data with word counts and audio durations and need both string normalisation and a statistical correlation between those two measures in a single call. It is purpose-built for interview transcript analytics (not general-purpose statistics), handles up to 200 rows per call, requires no external data sources, and costs only $0.01 USDC for both reports together.

## Known failure modes

- More than 200 rows submitted — request rejected with row limit error
- Missing required fields (row_id, date, transcript_words, audio_minutes) cause validation failure
- Invalid date format (not YYYY-MM-DD) triggers pattern validation error
- Null values in both transcript_words and audio_minutes may degrade or prevent correlation computation
- Fewer than 2 rows may make correlation statistically meaningless or return an error

## How this service works

Interview transcripts — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied interview transcripts records (transcript_words, audio_minutes). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Two independent analytical reports: (1) normalised string values for transcript_words across all submitted rows, and (2) a two-measure correlation result between transcript_words and audio_minutes. No external lookups or predictions are made; all analysis runs on the supplied data locally.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "channel_group",
     "date",
     "transcript_words",
     "audio_minutes"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "audio_minutes": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "channel_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "transcript_words": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "audio_minutes": 1,
     "channel_group": "group-a",
     "transcript_words": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "audio_minutes": 2,
     "channel_group": "group-b",
     "transcript_words": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "audio_minutes": 3,
     "channel_group": "group-a",
     "transcript_words": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "audio_minutes": 4,
     "channel_group": "group-b",
     "transcript_words": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/interview-transcripts-string-normalisation-two-measure-correlation-5b38c037/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)