Consumer Confidence in Czech Republic increased to 100.70 points in May from 97.70 points in April of 2025. This dataset provides - Czech Republic Consumer Confidence - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Dataset Card for Czech Subjectivity Dataset

  Dataset Summary

Czech subjectivity dataset (Subj-CS) of 10k manually annotated subjective and objective sentences from movie reviews and descriptions. See the paper description https://arxiv.org/abs/2204.13915

  Github

https://github.com/pauli31/czech-subjectivity-dataset

  Supported Tasks and Leaderboards

Subjectivity Analysis

  Languages

Czech

  Data Instances

train/dev/test… See the full description on the dataset page: https://huggingface.co/datasets/pauli31/czech-subjectivity-dataset.

Czech Republic Number of Households data was reported at 4,545,489.000 Unit in 2023. This records an increase from the previous number of 4,490,188.000 Unit for 2022. Czech Republic Number of Households data is updated yearly, averaging 4,458,737.500 Unit from Dec 2016 (Median) to 2023, with 8 observations. The data reached an all-time high of 4,545,489.000 Unit in 2023 and a record low of 4,347,840.000 Unit in 2016. Czech Republic Number of Households data remains active status in CEIC and is reported by Czech Statistical Office. The data is categorized under Global Database’s Czech Republic – Table CZ.H014: Households Statistic.

Home Czech DatasetCzechHigh-Quality Czech Call-Center and Spontaneous IVR Dataset for AI & Speech Models Contact Us OverviewTitleCzech Language DatasetDataset TypeSpontaneous IVRTotal hours200Sample Rate16 kHzCall center30016 kHzFeatured ClientsEmpowering teams to build…

The GlobalPhone corpus developed in collaboration with the Karlsruhe Institute of Technology (KIT) was designed to provide read speech data for the development and evaluation of large continuous speech recognition systems in the most widespread languages of the world, and to provide a uniform, multilingual speech and text database for language independent and language adaptive speech recognition as well as for language identification tasks. The entire GlobalPhone corpus enables the acquisition of acoustic-phonetic knowledge of the following 22 spoken languages: Arabic (ELRA-S0192), Bulgarian (ELRA-S0319), Chinese-Mandarin (ELRA-S0193), Chinese-Shanghai (ELRA-S0194), Croatian (ELRA-S0195), Czech (ELRA-S0196), French (ELRA-S0197), German (ELRA-S0198), Hausa (ELRA-S0347), Japanese (ELRA-S0199), Korean (ELRA-S0200), Polish (ELRA-S0320), Portuguese (Brazilian) (ELRA-S0201), Russian (ELRA-S0202), Spanish (Latin America) (ELRA-S0203), Swahili (ELRA-S0375), Swedish (ELRA-S0204), Tamil (ELRA-S0205), Thai (ELRA-S0321), Turkish (ELRA-S0206), Ukrainian (ELRA-S0377), and Vietnamese (ELRA-S0322).In each language about 100 sentences were read from each of the 100 speakers. The read texts were selected from national newspapers available via Internet to provide a large vocabulary. The read articles cover national and international political news as well as economic news. The speech is available in 16bit, 16kHz mono quality, recorded with a close-speaking microphone (Sennheiser 440-6). The transcriptions are internally validated and supplemented by special markers for spontaneous effects like stuttering, false starts, and non-verbal effects like laughing and hesitations. Speaker information like age, gender, occupation, etc. as well as information about the recording setup complement the database. The entire GlobalPhone corpus contains over 450 hours of speech spoken by more than 2100 native adult speakers.Data is shortened by means of the shorten program written by Tony Robinson. Alternatively, the data could be delivered unshorten.The Czech corpus was produced using the Ceskomoravsky Profit Journal and Lidove Noviny newspaper. It contains recordings of 102 speakers (57 males, 45 females) recorded in Prague, Czech Republic. The following age distribution has been obtained: 16 speakers are below 19, 70 speakers are between 20 and 29, 2 speakers are between 30 and 39, 9 speakers are between 40 and 49, and 5 speakers are over 50.

Key information about Czech Republic Liquid Assets Ratio

• Czech Republic Liquid Assets Ratio stood at 29.8 % in Jun 2024, compared with the previous figure of 27.8 % in Mar 2024
• Czech Republic Liquid Assets Ratio data is updated quarterly, available from Dec 2008 to Jun 2024
• The data reached an all-time high of 34.6 % in Jun 2014 and a record low of 13.8 % in Sep 2018

Until Q4 2018, liquid assets comprised only cash, claims payable on demand and liquid securities. The indicator was calculated on a consolidated basis. From Q1 2019, the supervisory definition of liquid assets is used. The indicator is calculated on an unconsolidated basis.


Further information about Czech Republic Liquid Assets Ratio

• In the latest report, Czech Republic Capital Adequacy Ratio was measured at 20.5 % in Jun 2024, compared with the previous update of 20.3 % in Mar 2024

Introduction

Welcome to the Czech Call Center Speech Dataset for the Travel domain designed to enhance the development of call center speech recognition models specifically for the Travel industry. This dataset is meticulously curated to support advanced speech recognition, natural language processing, conversational AI, and generative voice AI algorithms.

Speech Data:

This training dataset comprises 30 Hours of call center audio recordings covering various topics and scenarios related to the Travel domain, designed to build robust and accurate customer service speech technology.

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Topic Diversity

This dataset offers a diverse range of conversation topics, call types, and outcomes, including both inbound and outbound calls with positive, neutral, and negative outcomes.

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This extensive coverage ensures the dataset includes realistic call center scenarios, which is essential for developing effective customer support speech recognition models.

Transcription

To facilitate your workflow, the dataset includes manual verbatim transcriptions of each call center audio file in JSON format. These transcriptions feature:

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These ready-to-use transcriptions accelerate the development of the Travel domain call center conversational AI and ASR models for the Czech language.

Metadata

The dataset provides comprehensive metadata for each conversation and participant:

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This metadata is a powerful tool for understanding and characterizing the data, enabling informed decision-making in the development of Czech call center speech recognition models.

Usage and Applications

This dataset can be used for various applications in the fields of speech recognition, natural language processing, and conversational AI, specifically tailored to the Travel domain. Potential use cases include:

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Secure and Ethical Collection

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Updates and Customization

Understanding the importance of diverse environments for robust ASR models, our call center voice dataset is regularly updated with new audio data captured in various real-world conditions.

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License

This Travel domain call center audio dataset is created by FutureBeeAI and is available for commercial use.

Graph and download economic data for Broad Effective Exchange Rate for Czech Republic (NBCZBIS) from Jan 1994 to Apr 2025 about Czech Republic, broad, exchange rate, currency, rate, and indexes.

Key information about Czech Republic Private Consumption: % of GDP

• Czech Republic Private Consumption accounted for 45.9 % of its Nominal GDP in Dec 2022, compared with a ratio of 46.7 % in the previous quarter.
• Czech Republic Private Consumption contribution to Nominal GDP ratio is updated quarterly, available from Mar 1995 to Dec 2022, with an average share of 48.6 %.
• The data reached an all-time high of 51.9 % in Mar 1999 and a record low of 42.6 % in Dec 2020.

CEIC calculates Private Consumption as % of Nominal GDP from quarterly Private Consumption Expenditure and quarterly Nominal GDP. Private Consumption Expenditure is calculated as the sum of Household and NPISHs Consumption. Czech Statistical Office provides Private Consumption Expenditure in local currency and Nominal GDP in local currency.


Related information about Czech Republic Private Consumption: % of GDP

• In the latest reports, Czech Republic GDP expanded 0.2 % YoY in Dec 2022.
• Its Nominal GDP reached 72.0 USD bn in Dec 2022.
• Czech Republic GDP Per Capita reached 26,805.6 USD in Dec 2021.
• Its Gross Savings Rate was measured at 31.5 % in Dec 2022.

Graph and download economic data for Population, Total for Czech Republic (POPTOTCZA647NWDB) from 1960 to 2023 about Czech Republic and population.

Graph and download economic data for Interest Rates: Long-Term Government Bond Yields: 10-Year: Main (Including Benchmark) for Czech Republic (IRLTLT01CZQ156N) from Q2 2000 to Q1 2025 about Czech Republic, long-term, 10-year, bonds, yield, government, interest rate, interest, and rate.

Graph and download economic data for Benchmarked Value Added - Market Services for the Czech Republic (DISCONTINUED) (ULQBBV07CZQ189N) from Q1 1995 to Q2 2011 about Czech Republic, unit labor cost, value added, labor, and services.

Czech Republic manufacturing output for 2023 was 70.73 billion US dollars, a 15.97% increase from 2022.

<ul style='margin-top:20px;'>

<li>Czech Republic manufacturing output for 2022 was <strong>60.99 billion US dollars</strong>, a <strong>2.69% increase</strong> from 2021.</li>
<li>Czech Republic manufacturing output for 2021 was <strong>59.40 billion US dollars</strong>, a <strong>13.09% increase</strong> from 2020.</li>
<li>Czech Republic manufacturing output for 2020 was <strong>52.52 billion US dollars</strong>, a <strong>8.05% decline</strong> from 2019.</li>
</ul>Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current U.S. dollars.

Foreign Direct Investment in Czech Republic increased by 4971237.05 CZK Million in 2023. This dataset provides - Czech Republic Foreign Direct Investment - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Production: Industry: Total Industry Excluding Construction for Czech Republic (PRINTO01CZQ657S) from Q2 1990 to Q1 2025 about Czech Republic, IP, and construction.

BASIC INFORMATION

Czech Text Document Corpus v 2.0 is a collection of text documents for automatic document classification in Czech language. It is composed of the text documents provided by the Czech News Agency and is freely available for research purposes. This corpus was created in order to facilitate a straightforward comparison of the document classification approaches on Czech data. It is particularly dedicated to evaluation of multi-label document classification approaches, because one document is usually labelled with more than one label. Besides the information about the document classes, the corpus is also annotated at the morphological layer.

The main part (for training and testing) is composed of 11,955 real newspaper articles. We provide also a development set which is intended to be used for tuning of the hyper-parameters of the created models. This set contains 2735 additional articles.

The total category number is 60 out of which 37 most frequent ones are used for classification. The reason of this reduction is to keep only the classes with the sufficient number of occurrences to train the models.

Technical Details

Text documents are stored in the individual text files using UTF-8 encoding. Each filename is composed of the serial number and the list of the categories abbreviations separated by the underscore symbol and the .txt suffix. Serial numbers are composed of five digits and the numerical series starts from the value one.

For instance the file 00046_kul_nab_mag.txt represents the document file number 46 annotated by the categories kul (culture), nab (religion) and mag (magazine selection). The content of the document, i.e. the word tokens, is stored in one line. The tokens are separated by the space symbols.

Every text document was further automatically mophologically analyzed. This analysis includes lemmatization, POS tagging and syntactic parsing. The fully annotated files are stored in .conll files. We also provide the lemmatized form, file with suffix .lemma, and appropriate POS-tags, see .pos files. The tokenized version of the documents is also available in .tok files.

This corpus is available only for research purposes for free. Commercial use in any form is strictly excluded.

Vystadial 2013 is a dataset of telephone conversations in English and Czech, developed for training acoustic models for automatic speech recognition in spoken dialogue systems. It ships in three parts: Czech data, English data, and scripts.

The data comprise over 41 hours of speech in English and over 15 hours in Czech, plus orthographic transcriptions. The scripts implement data pre-processing and building acoustic models using the HTK and Kaldi toolkits.

This is the Czech data part of the dataset.

Graph and download economic data for OECD based Recession Indicators for the Czech Republic from the Peak through the Period preceding the Trough (DISCONTINUED) (CZERECDP) from 1995-02-01 to 2022-08-31 about Czech Republic, peak, trough, and recession indicators.

This is the Czech Court Decisions Corpus (CzCDC 1.0). This corpus contains whole texts of the decisions from three top-tier courts (Supreme, Supreme Administrative and Constitutional court) in Czech republic. Court decisions are published from 1st January 1993 to 30th September 2018.

The language of decisions is Czech. Content of decisions is unedited and obtained directly from the competent court.

Decisions are in .txt format in three folders divided by courts.

Corpus contains three .csv files containing the list of all decisions with four columns: - name of the file: exact file name of a decision with extension .txt; - decision identifier (docket number): official identification of the decision as issued by the court; - date of decision: in ISO 8601 (YYYY-MM-DD); - court abbreviation: SupCo for Supreme Court, SupAdmCo for Supreme Administrative Court, ConCo for Constitutional Court

Statistics: - SupCo: 111 977 decisions, 23 699 639 lines, 224 061 129 words, 1 462 948 200 bits; - SupAdmCo: 52 660 decisions, 18 069 993 lines, 137 839 985 words, 1 067 826 507 bits; - ConCo: 73 086 decisions, 6 178 371 lines, 98 623 753 words, 664 657 755 bits - all courts combined: 237 723 decisions, 47 948 003 lines, 460 524 867 words, 3 195 432 462 bits