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Viola On-Site Voice Data Collection - Telugu Speakers, Hyderabad

Company
Company DataForce
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary $55 USD
Location
Location Hyderabad, India
Posted Date
Posted Date Today
Fluent Telugu clear articulation good listening basic tech comfort with earbuds and audio devices punctuality ability to converse naturally willingness to follow prompts
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• Must be 18 years or older. • Must have idiomatic fluency in Telugu (native or near‑native speaking ability). • Must be able to travel to the DataForce office in Hyderabad, India for the scheduled session. • Must be willing to engage in a recorded conversation with another participant. • No specific academic degree or branch is required; the study is open to all qualified individuals. • No minimum percentage or CGPA criteria. • No backlog restrictions as this is not a conventional employment role.

1
Round 1: Application submission and eligibility verification
2
Round 2: Scheduling and on‑site verification (no formal interview)
3
Round 3: Participation in the recording session (completion of the study)
4
Compensation disbursal
TransPerfect is the world’s largest privately‑held language and technology solutions provider, serving Fortune‑500 companies across more than 100 cities. Its DataForce division specializes in high‑quality data collection, annotation and validation services that power AI‑driven products such as virtual assistants, chatbots, and speech‑to‑text engines. By leveraging a global crowd of native speakers, DataForce helps clients improve the accuracy and cultural relevance of their language models. The organization prides itself on a collaborative, research‑oriented culture where data collectors work closely with linguists, engineers, and product managers to shape the next generation of intelligent systems. The Viola On‑Site Voice Data Collection study is a short‑term, paid research project aimed at gathering natural conversational audio from native Telugu speakers. Participants will be paired with another fluent speaker and engage in a guided dialogue lasting up to two and a half hours. The conversation will be recorded through earbuds, with prompts covering everyday topics such as shopping, weather, and personal opinions. The recordings will later be used to train and fine‑tune voice recognition algorithms for virtual assistants, ensuring they understand regional accents and colloquial expressions. Key responsibilities include: 1. Arriving at the Hyderabad DataForce premises on the scheduled date and time. 2. Completing a brief consent and demographic form before the session. 3. Wearing the provided earbuds and following the facilitator’s prompts. 4. Engaging in a natural, unscripted conversation with a fellow participant. 5. Maintaining a clear and audible speaking style throughout the recording. 6. Providing honest feedback on the recording experience when asked. 7. Ensuring no background noise or interruptions interfere with the audio capture. 8. Adhering to all confidentiality and data‑privacy guidelines. 9. Collecting the compensation payment method details (PayPal, Gift Card, or Wire Transfer). 10. Leaving the venue after the session is completed. The technical stack is minimal for participants – a pair of high‑quality earbuds, a laptop or tablet for the facilitator’s prompts, and a quiet, controlled environment. Behind the scenes, DataForce uses industry‑standard audio capture software, cloud storage with encryption, and annotation tools that linguists later employ to label speech segments. Growth path: While this is a one‑time study, participants gain exposure to the AI data‑collection ecosystem and may be invited to future higher‑paid projects, including multilingual annotation, transcription, and quality‑control roles. Successful contributors often transition into part‑time or freelance positions within DataForce’s broader talent pool. Why join? Apart from the immediate $55 reward, participants help improve technology that millions rely on daily, especially in regional language markets. The study offers a professional, safe environment, flexible scheduling, and the chance to be part of a global effort to make voice assistants more inclusive for Telugu speakers.

DataForce — Software Engineering & Full Stack Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC 📖
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

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Comprehensive guide covering typical interview formats, common questions, and preparation tips for DataForce and off-campus tech roles.

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Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

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CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

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Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Fluent Telugu, clear articulation, good listening, basic tech comfort with earbuds and audio devices, punctuality, ability to converse naturally, willingness to follow prompts) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
DataForce Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
Explain OOP (Object-Oriented Programming) principles with real-world examples in Fluent Telugu. Answer ▼
Model Answer: 1. Encapsulation (data hiding via private fields/getters). 2. Abstraction (hiding implementation complexity). 3. Inheritance (code reusability). 4. Polymorphism (method overriding/overloading).
What is the time and space complexity of QuickSort vs MergeSort? Answer ▼
Model Answer: QuickSort: Average O(N log N) time, O(log N) space. Worst O(N^2). MergeSort: Guaranteed O(N log N) time, but requires O(N) auxiliary space.
Explain the difference between SQL Indexing (B-Tree vs Hash) and when not to use an index. Answer ▼
Model Answer: Indexes speed up SELECT queries via B-Trees. However, they slow down INSERT, UPDATE, and DELETE operations because indexes must be updated on disk. Avoid on low-cardinality columns (e.g., boolean flags).
What happens under the hood when you enter a URL in a browser? Answer ▼
Model Answer: 1. DNS lookup (resolves IP). 2. TCP 3-way handshake (SYN, SYN-ACK, ACK). 3. TLS negotiation for HTTPS. 4. HTTP GET request sent. 5. Server responds with HTML/CSS/JS. 6. Browser renders DOM & CSSOM tree.
What is the difference between REST and GraphQL APIs? Answer ▼
Model Answer: REST uses multiple fixed endpoints with possible over/under-fetching. GraphQL uses a single endpoint allowing clients to query exact fields in a single request.
Why do you want to join DataForce as a Viola On-Site Voice Data Collection - Telugu Speakers, Hyderabad?
Preparation Tip: Highlight DataForce's market reputation, recent tech innovations, and how your skills in Fluent Telugu directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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