Interview scoring utilizes six advanced algorithms, some customizable during interview setup, and others leveraging pre-defined scoring bands for consistent, insightful results.Interview creation#
In JobMojito, interviews can be created in two ways:1.
Automatically using a large language model. Based on the job title, job description, and additional metadata, the platform generates an1.
interview sequence, ****a set of questions that will be asked by the avatar during the interview. These include test questions to ensure the candidate has at least a basic understanding of the field they’re applying for
2.
Candidate expectations, which are hidden criteria outlining what is expected from the candidate’s profile
2.
Manually, where recruiters define both the interview sequence and candidate expectations themselves.
Customizing scoring weights#
Before publishing the interview, recruiters can customize the scoring weights for each algorithm that JobMojito runs. If a score is set to 0, that specific algorithm will not be executed for any candidate in the interview.Maximum Number of Attempts: Allows candidates to retake the interview multiple times.
Disable Retry When User Reaches a Score: When enabled with multiple attempts, this feature prevents further retries once the candidate achieves a specified score—helping candidates avoid unnecessary attempts for minimal score improvements.
Weights of Each Score Relative to Overall Score: Determines how much each individual score contributes to the overall result, letting you fine-tune the impact of each evaluated area.
Scoring Calculation#
This section is describing, how individual scores are calculatedAI analysis of full conversation#
Is LLM based scoring method that is executed, once full interview is completedFull transcript of the interview
Score 1: for candidates that you would never hire based on their responses
Score 5: for average candidates or candidates that didn’t completed the full interview
Score 10: for candidates you would hire on the spot without any further testing
AI analysis of individual answers#
LLM-based scoring is applied to each individual question and answer, ensuring precise evaluation of candidate responses.Output is score between 1-5 (translated into score between 1-10)Score 1: The answer missed the point
Score 2: Partially addresses the question but lacks key details
Score 3: Adequate and correct
Score 4: A strong answer that goes beyond the basic requirements of the question
Score 5: Demonstrates expertise, creativity, or exceptional depth
AI Resume analysis (turned off by default)#
This feature uses LLM-based scoring to evaluate the candidate’s plaintext resume against the job position.Score 0: Candidate doesn’t have any suitable experiences
Score 10: Candidate is amazing fit to the job position
Speech sentiment#
This is a text-based assessment of the candidate’s answer, conducted for each individual response.Text of the candidate answer
Sentiment between -1 and 1
Score 0: When sentiment is -0.2 or lower
Score 10: When sentiment is 0.3 and higher
Speech pronunciation#
Audio analysis compares the candidate’s raw audio input against a native speaker’s voice profile. This analysis is performed for each of the candidate’s answers.Candidate response audio data
AccuracyScore: Pronunciation accuracy of the speech. Accuracy indicates how closely the phonemes match a native speaker's pronunciation. Syllable, word, and full text accuracy scores are aggregated from the phoneme-level accuracy score, and refined with assessment objectives.
FluencyScore: Fluency of the given speech. Fluency indicates how closely the speech matches a native speaker's use of silent breaks between words.
CompletenessScore: Completeness of the speech, calculated by the ratio of pronounced words to the input reference text.
ProsodyScore: Prosody of the given speech. Prosody indicates how natural the given speech is, including stress, intonation, speaking speed, and rhythm.
Score: Overall score of the pronunciation quality of the given speech. Is calculated from AccuracyScore, FluencyScore, CompletenessScore, and ProsodyScore with weight, provided that ProsodyScore and CompletenessScore are available.
Speech cadence#
During speech-to-text transcription, the platform records the exact millisecond each word is spoken. This data is converted into an industry-standard words-per-minute score, calculated using a purely mathematical formula.Score 1: When words per minute is less than 80 or more than 220
Score 10: When words per minute is between 100-130
Modified at 2025-06-26 10:01:47
