Criar esquemas para áudio - Amazon Bedrock

As traduções são geradas por tradução automática. Em caso de conflito entre o conteúdo da tradução e da versão original em inglês, a versão em inglês prevalecerá.

Criar esquemas para áudio

De modo semelhante aos esquemas de imagem, só é possível ter um esquema de áudio por projeto.

Abaixo são apresentados alguns exemplos de campo para processamento de áudio.

Exemplos de campos de esquema para arquivos de áudio

Campo Instrução Tipo de extração Tipo
transcript_summary Generate a concise abstractive summary of the conversation, focusing on the main topics and key themes. Ensure accuracy by summarizing only what is explicitly discussed, without adding specific details not present in the conversation. Keeping the response within 100 words. inferred string
topics The main topics of the audio transcript, listed as single words. inferred [string] (Array of strings)
category The category of the audio (not the topic). Choose from General conversation, Media, Hospitality, Speeches, Meetings, Education, Financial, Public sector, Healthcare, Sales, Audiobooks, Podcasts, 911 calls, Other. inferred string
spoken_named_entities Any named entities (typically proper nouns) explicitly mentioned in the audio transcript including locations, brand names, company names, product names, services, events, organizations, etc. Do not include names of people, email addresses or common nouns. extractive [string] (Array of strings)

Exemplos de campos de esquema para analytics conversacional

Campo Instrução Tipo de extração Tipo
call_summary Summarize the caller-agent conversation in under 100 words. Start with the caller's request, then the agent's response and actions, ending with outcomes or follow-ups. Include key details like emails, links, or callbacks. For multiple issues, summarize each with its outcome and next steps. inferred string
call_categories The category (or categories) of the call. Choose one or more from Billing, Tech support, Customer service, Account support, Sales, Complaints, Product issues, Service issues, General inquiries, Other. inferred [string] (Array of strings)
spoken_locations Locations explicitly mentioned in the conversation, including cities, states, and countries. extractive [string]
call_opening Did the agent greet the caller and introduce themselves at the beginning of the call? extractive boolean