AssemblyAI Unveils C# .NET SDK for Advanced Audio Transcription and Analysis

AssemblyAI
has
announced
the
release
of
its
new
C#
.NET
SDK,
designed
to
facilitate
audio
transcription
and
analysis
for
developers
utilizing
.NET
languages
such
as
C#,
VB.NET,
and
F#.
The
SDK
aims
to
streamline
the
use
of
AssemblyAI’s
advanced
Speech
AI
models,
according
to

AssemblyAI.

Key
Features
and
Goals

The
SDK
has
been
developed
with
several
key
objectives
in
mind:

• Provide
  an
  intuitive
  interface
  for
  all
  AssemblyAI
  models
  and
  features
  using
  idiomatic
  C#.
• Ensure
  compatibility
  with
  multiple
  frameworks,
  including
  .NET
  6.0,
  .NET
  Framework
  4.6.2,
  and
  .NET
  Standard
  2.0
  and
  above.
• Minimize
  dependencies
  to
  prevent
  version
  conflicts
  and
  the
  need
  for
  binding
  redirects.

Transcribing
Audio
Files

One
of
the
primary
functionalities
of
the
SDK
is
audio
transcription.
Developers
can
transcribe
audio
files
asynchronously
or
in
real-time.
Below
is
an
example
of
how
to
transcribe
an
audio
file:

using AssemblyAI;
using AssemblyAI.Transcripts; var client = new AssemblyAIClient("YOUR_API_KEY"); var transcript = await client.Transcripts.TranscribeAsync(new TranscriptParams
{ AudioUrl = "https://storage.googleapis.com/aai-docs-samples/nbc.mp3"
}); transcript.EnsureStatusCompleted(); Console.WriteLine(transcript.Text);

For
local
files,
similar
code
can
be
used
to
achieve
transcription.

await using var stream = new FileStream("./nbc.mp3", FileMode.Open);
var transcript = await client.Transcripts.TranscribeAsync( stream, new TranscriptOptionalParams { LanguageCode = TranscriptLanguageCode.EnUs }
); transcript.EnsureStatusCompleted(); Console.WriteLine(transcript.Text);

Real-Time
Audio
Transcription

The
SDK
also
supports
real-time
audio
transcription
using
Streaming
Speech-to-Text.
This
feature
is
particularly
useful
for
applications
requiring
immediate
processing
of
audio
data.

using AssemblyAI.Realtime; await using var transcriber = new RealtimeTranscriber(new RealtimeTranscriberOptions
{ ApiKey = "YOUR_API_KEY", SampleRate = 16_000
}); transcriber.PartialTranscriptReceived.Subscribe(transcript =>
{ Console.WriteLine($"Partial: {transcript.Text}");
});
transcriber.FinalTranscriptReceived.Subscribe(transcript =>
{ Console.WriteLine($"Final: {transcript.Text}");
}); await transcriber.ConnectAsync(); // Pseudocode for getting audio from a microphone for example
GetAudio(async (chunk) => await transcriber.SendAudioAsync(chunk)); await transcriber.CloseAsync();

Utilizing
LeMUR
for
LLM
Applications

The
SDK
integrates
with
LeMUR
to
allow
developers
to
build
large
language
model
(LLM)
applications
on
voice
data.
Here
is
an
example:

var lemurTaskParams = new LemurTaskParams
{ Prompt = "Provide a brief summary of the transcript.", TranscriptIds = [transcript.Id], FinalModel = LemurModel.AnthropicClaude3_5_Sonnet
}; var response = await client.Lemur.TaskAsync(lemurTaskParams); Console.WriteLine(response.Response);

Audio
Intelligence
Models

Additionally,
the
SDK
comes
with
built-in
support
for
audio
intelligence
models,
enabling
sentiment
analysis
and
other
advanced
features.

var transcript = await client.Transcripts.TranscribeAsync(new TranscriptParams
{ AudioUrl = "https://storage.googleapis.com/aai-docs-samples/nbc.mp3", SentimentAnalysis = true
}); foreach (var result in transcript.SentimentAnalysisResults!)
{ Console.WriteLine(result.Text); Console.WriteLine(result.Sentiment); // POSITIVE, NEUTRAL, or NEGATIVE Console.WriteLine(result.Confidence); Console.WriteLine($"Timestamp: {result.Start} - {result.End}");
}

For
more
information,
visit
the

official
AssemblyAI
blog.

Image
source:
Shutterstock