What is Audio Annotation?

Audio annotation is the process of making sound and speech, stored in any format, understandable and comprehensible to AI models. It plays a critical role in developing applications like virtual assistants, chatbots, and other Natural Language Processing (NLP) technologies that aim to mimic or augment human interaction. Audio transcription enables the labeling of audio datasets, including environmental noise, conversations, and even machine sounds. Proper labeling and tagging of these audio datasets help machine learning models make sense of the sounds. Audio annotation also includes identifying various languages, nuances, dialects, speaker demographics, and transcriptions of specific pronunciation and intonation.

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Our Audio Annotation Services

Speech-to-Text Transcription

An integral part of the NLP technology, speech-to-text transcription involves transcribing recorded speech into text format while accurately labeling words and sounds. aiTouch's annotation experts transcribe audio recordings of varying quality while accounting for tricky factors such as background noise that compromise audio quality. Be it intonation, pronunciation, punctuation, etc., our experts carefully labeled each to create qualitative datasets for machine training and development.

Sound Labeling

aiTouch uses cutting-edge audio annotation tools to understand audio files and recorded sounds comprehensively. These enable accurate tagging by isolating the identified sounds and labeling them with specific metadata to make the training datasets more inclusive and meaningful for the AI models.

Event Tracking

Our audio annotation experts evaluate the performance of the sound event detection systems where sound sources are rarely heard in isolation, much like everyday life. This form of audio annotation requires complete diligence. There can be no control over the number of overlapping sound events at each stage - not at the time of testing the audio data nor during machine training.

Audio Classification

Our analysts help classify audio datasets into predetermined categories by carefully listening to & analyzing audio recordings. Vital to the development of virtual assistants, automatic speech recognition, and text to speech format, our audio classification services help companies train their machines to differentiate between sounds and voice commands correctly.

Intent Analysis

aiTouch's analysts bring together the various components of Natural Language Utterance (NLU) - semantics, dialects, context, stress, etc., to drive the development of next-gen digital assistants, chatbots, and conversational AI products in healthcare, retail, finance, tech, and media.

Multi-Label Annotation

The aiTouch analysts annotate audio data using multiple labels to help AI models differentiate overlapping audio sources. It allows machines to learn to discern that an audio dataset might belong to one or multiple classes, leading to better decision-making.

Speaker Recognition

At aiTouch, we use next-gen annotation techniques to partition the input audio file into homogeneous audio segments based on specific sources, such as the speaker's identity, music, silence, or background noise. Our service enables us to automate analyzing any conversation/speech, including call center communication.

Emotion Annotation

We analyze your text data and assign specific Parts of Speech (POS) tags to each word, covering the functional elements of speech like identifying adjectives, adverbs, verbs, pronouns, punctuation, prepositions, adjectives, etc., in a sentence. Sentiment analysis and classification are the most common use case for this type of text annotation.

Sentiment Analysis

Understanding whether a segment of speech is perceived as positive, negative, or neutral is very important for developing chatbots, virtual assistants, and other conversational AI models. Our analysts identify trends and develop the clients’ brands using advanced sentiment analysis solutions. Domain experts annotate the audio data to interpret nuances in product reviews, social media, financial updates, etc., to provide additional information to the AI models.

Speech Annotation Quality Assessment

Our expert audio annotators use next-gen tools to determine the quality of the accuracy and interpretation consistency of the annotated speech vis-a-vis the annotation guidelines. We help resolve ambiguities in the audio files, correct transcription errors, improve the overall quality of audio files, and create a database of audio clips useful for various purposes.

Why aiTouch

Training machines to understand and correctly interpret the visual world requires a high volume of precisely and accurately labeled training data. Experience, expertise, and access to state-of-the-art tools are crucial as AI programs can function optimally only with concisely labeled data. Data that is customized to your project and specific data training needs. Data that delivers the best cost: quality ratio. That’s where we come in.

aiTouch is your one-stop solution for all your data-related needs, from bounding boxes, polygons, and landmarking to semantic segmentation and panoptic annotation. We provide high-quality annotated video data for object classification, detection, localization, and segmentation in various use cases. We tailor our specialized portfolio of end-to-end annotation services and solutions to cater to your AI model training needs. Our highly skilled data annotators apply best practices and in-house next-gen video annotation & labeling tools to deliver world-class training data to our clients worldwide. We combine people and technology to create data that powers AI and automation while maintaining complete data security and confidentiality.

In-house Annotation and Labeling Tool

State-of-the-art in-house tool capable of performing various types of annotation & labeling

Competitive Pricing

Cost-effective services delivered within budget, ensuring the best cost: quality ratio

Quality with Accuracy

Multiple stages of auditing & reviewing to deliver high quality & accurate datasets

Enhanced Data Security & Privacy

Follow best practices to deliver high standards of data security & safeguard customers’ privacy

Highly Scalable Service

Proven ability to deliver accurate & high-performing data across use cases, scaling as per client need

Speedy Delivery

Proven processes & next-gen tools that deliver high-quality training data at greater speed

Powerful APIs

Powerful API integration to connect with clients’ existing MLOPs infrastructure

Full Spectrum Labeling

Supports static and dynamic labeling to capture complex object changes over time. Availability of customized classes and multiple attributes per instance

Domains That Use Audio Annotation Services

Healthcare

Audio annotation helps elicit valuable insights from the healthcare database – medical records, digital documents, and clinical data to power Robotic Process Automation (RPA), virtual assistants, and medical decision support algorithms. These improve patient outcomes, manage compliance, and streamline operations, revolutionizing medical diagnosis and treatment.

Legal

Audio transcription specialists in the legal domain transcribe audio footage to text format from mounds of legal briefs, court hearings, interrogation, client depositions, and general legal correspondence. Audio annotation helps automate this arduous process, saving valuable time and resources.

Finance

Transcribed audio files help customers improve business operations like performance discussions, periodic meetings, and future strategies by leveraging machine learning and RPA. It can transform complex documents into actionable intelligence leading to enhanced customer experience.

Insurance

Accurate and precise audio annotation and transcription of recorded statements, interaction with legal & medical professionals, theft/property damage reports for insurance inquiry, etc., helps insurance companies become more efficient and minimize their risk quotient.

Government

Audio annotation offers the ideal solution for handling sensitive data that requires secure processing. Trained analysts transcribe the audio footage to text format from court proceedings, witness statements, hearings, and dictations from vast government databases to enable process automation.

Commerce

Audio annotation in the trading domain helps analyze customer sentiment and intent via reviews and comments. It provides optimized training data for AI & ML models, making innovative consumer experiences in the retail space more plausible. It also helps in mining useful information from unstructured audio data to improve customer experience.

Media & Entertainment

Social media platforms are influential and vast sources of valuable consumer stories and opinions. Audio transcription and speech recognition is widely used by podcasters, entertainers, public speakers, and others in the media space. They can transcribe podcasts, apply speech recognition to online calls, create closed captioning file types with timestamps for audio/video files, optimize them for playback on mobile devices, and so much more.