# Transcribe and Score Recording — Speechace

> Transcribes and scores a provided speech recording. See the documentation

- Key: `speechace-transcribe-and-score-recording`
- Type: Action (Write)
- Version: 0.0.4
- App: Speechace (`speechace`) — https://pipedream.com/apps/speechace.md
- This page (HTML): https://pipedream.com/apps/speechace/actions/transcribe-and-score-recording
- Hints: open-world
- Source: https://github.com/PipedreamHQ/pipedream/blob/master/components/speechace/actions/transcribe-and-score-recording/transcribe-and-score-recording.mjs

## Description

Transcribes and scores a provided speech recording. [See the documentation](https://docs.speechace.com/#76089b5d-7e25-4744-8d32-f6c230acf217)

## Props

| Prop | Type | Required | Description |
|---|---|---|---|
| `filePath` | `string` | Yes | Provide either a file URL or a path to a file in the /tmp directory (for example, /tmp/myFile.pdf). |
| `relevanceContext` | `string` | No | Question Prompt text provided to the user. When this parameter is passed, the relevance of the user audio transcript is evaluated given the relevance_context and a resulting relevance class is returned in .speech_score.relevance.class |
| `dialect` | `string` | No | The dialect to use for scoring |
| `userId` | `string` | No | A unique anonymized identifier for the end-user who spoke the audio |
| `syncDir` | `dir` | No | SyncDir |

## Run it

**MCP**

```ts
import { Client } from "@modelcontextprotocol/sdk/client/index.js"
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js"
import { PipedreamClient } from "@pipedream/sdk"

const pd = new PipedreamClient({
  projectId: process.env.PIPEDREAM_PROJECT_ID!,
  clientId: process.env.PIPEDREAM_CLIENT_ID!,
  clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
  projectEnvironment: "production",
})

const accessToken = await pd.rawAccessToken

const transport = new StreamableHTTPClientTransport(
  new URL("https://remote.mcp.pipedream.net/v3"),
  {
    requestInit: {
      headers: {
        Authorization: `Bearer ${accessToken}`,
        "x-pd-project-id": process.env.PIPEDREAM_PROJECT_ID!,
        "x-pd-environment": "production",
        "x-pd-external-user-id": "{external_user_id}", // any stable ID for this user in your system
        "x-pd-app-slug": "speechace",
      },
    },
  },
)

const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)

const { tools } = await mcp.listTools()

// listTools() hands your model this tool's input schema, so it can
// fill the arguments itself:
const result = await mcp.callTool({
  name: "speechace-transcribe-and-score-recording",
  arguments: {
    filePath: "File Path or URL",
    relevanceContext: "Relevance Context",
  },
})
```

**TypeScript**

```ts
import { PipedreamClient } from "@pipedream/sdk"

const pd = new PipedreamClient({
  projectId: process.env.PIPEDREAM_PROJECT_ID!,
  clientId: process.env.PIPEDREAM_CLIENT_ID!,
  clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
  projectEnvironment: "production",
})

const result = await pd.actions.run({
  id: "speechace-transcribe-and-score-recording",
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  configuredProps: {
    speechace: { authProvisionId: "apn_xxxxxxx" },
    filePath: "File Path or URL",
    relevanceContext: "Relevance Context",
  },
})

console.log(result)
```

**cURL**

```bash
curl -X POST https://api.pipedream.com/v1/connect/{project_id}/actions/run \
  -H "Content-Type: application/json" \
  -H "X-PD-Environment: production" \
  -H "Authorization: Bearer {access_token}" \
  -d '{
    "external_user_id": "{external_user_id}",
    "id": "speechace-transcribe-and-score-recording",
    "configured_props": {
      "speechace": { "authProvisionId": "apn_xxxxxxx" },
      "filePath": "File Path or URL",
      "relevanceContext": "Relevance Context"
    }
  }'
```

---

- App: https://pipedream.com/apps/speechace.md · All apps: https://pipedream.com/apps