Use when writing or reviewing Java code in this repo that enables Deepgram intelligence overlays on `/v1/listen` audio transcription - diarization, entity detection, sentiment, summarize, topics, intents, language detection, and redaction. Same endpoint as plain STT, but with extra request fields on `ListenV1RequestUrl` or `MediaTranscribeRequestOctetStream`. Use `deepgram-java-speech-to-text` for plain transcripts and `deepgram-java-text-intelligence` for analysis on existing text. Triggers include "audio intelligence", "diarize", "summarize audio", "sentiment from audio", "topic detection", and "redact".
88
82%
Does it follow best practices?
Impact
100%
1.13xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Audio intelligence is not a separate client in this SDK. It is the Listen V1 REST request surface with additional analysis fields enabled.
Use a different skill when:
deepgram-java-speech-to-text.deepgram-java-text-intelligence.deepgram-java-conversational-stt.import com.deepgram.DeepgramClient;
DeepgramClient client = DeepgramClient.builder()
.apiKey(System.getenv("DEEPGRAM_API_KEY"))
.build();import com.deepgram.resources.listen.v1.media.requests.ListenV1RequestUrl;
import com.deepgram.resources.listen.v1.media.types.MediaTranscribeRequestModel;
import com.deepgram.resources.listen.v1.media.types.MediaTranscribeResponse;
ListenV1RequestUrl request = ListenV1RequestUrl.builder()
.url("https://dpgr.am/spacewalk.wav")
.model(MediaTranscribeRequestModel.NOVA3)
.smartFormat(true)
.punctuate(true)
.diarize(true)
.language("en-US")
.build();
MediaTranscribeResponse result = client.listen().v1().media().transcribeUrl(request);The concrete repo example (examples/listen/AdvancedOptions.java) demonstrates the same pattern for enabling higher-value Listen options via the builder.
The generated ListenV1RequestUrl and MediaTranscribeRequestOctetStream classes also expose these verified analysis fields in this checkout:
sentimentsummarizetopicscustomTopiccustomTopicModeintentscustomIntentcustomIntentModedetectEntitiesdetectLanguagediarizeredactimport com.deepgram.resources.listen.v1.websocket.V1ConnectOptions;
import com.deepgram.resources.listen.v1.websocket.V1WebSocketClient;
import com.deepgram.types.ListenV1Model;
import java.util.concurrent.TimeUnit;
V1WebSocketClient wsClient = client.listen().v1().v1WebSocket();
wsClient.onResults(result -> System.out.println(result));
wsClient.connect(V1ConnectOptions.builder()
.model(ListenV1Model.NOVA3)
.diarize(true)
.build())
.get(10, TimeUnit.SECONDS);In this Java checkout, the WebSocket connect options include diarize, detectEntities, redact, and the normal streaming transcription controls, but not summarize, topics, intents, or detectLanguage.
ListenV1RequestUrl and MediaTranscribeRequestOctetStreamsentiment, summarize, topics, customTopic, customTopicMode, intents, customIntent, customIntentMode, detectEntities, detectLanguage, diarize, redactsmartFormat, punctuate, paragraphs, utterances, numerals, keywords, keyterm, replace, searchdiarize, detectEntities, redact, plus standard live transcription optionssrc/main/java/com/deepgram/resources/listen/v1/media/requests/ and src/main/java/com/deepgram/resources/listen/v1/websocket/ plus examples/listen/AdvancedOptions.java. reference.md is absent here./llmstxt/developers_deepgram_llms_txtsummarize, topics, intents, or detectLanguage.summarize on Listen V1 is its own generated type. Do not assume the Read API shape is identical.redact is currently a single String field on the REST builders. Do not assume Python-style string-or-list support here.NOVA3; follow that unless you have verified another model supports the overlays you need.examples/listen/AdvancedOptions.javaexamples/listen/TranscribeUrl.javaexamples/listen/FileUploadTypes.javaFor cross-language Deepgram product knowledge — the consolidated API reference, documentation finder, focused runnable recipes, third-party integration examples, and MCP setup — install the central skills:
npx skills add deepgram/skillsThis SDK ships language-idiomatic code skills; deepgram/skills ships cross-language product knowledge (see api, docs, recipes, examples, starters, setup-mcp).
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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.